20190401Annual Report.pdf

Aliutsra
Avista Corp.
141 1 East Mission P .O. Box 3727
Spokane. Washington 99220-0500
Telephone [phone]
Toll Free 800-727-9170
March 29,2019
Diane Hanian, Secretary
Idaho Public Utilities Commission
Statehouse Mail
W . 472 Washington Street
Boise, Idaho 83720 Av ta- E - t3- 02
RE: Avista Utilities 2018 Annual Report Regarding Selected Research and Development
Efficiency Projects
Dear Ms. Hanian:
Enclosed for filing with the Commission is an original andT copies of Avista Corporation's dba
Avista Utilities ("Avista or the Company") Report on the Company's selected electric energy
efficiency research and development (R&D) projects, implemented by the state of Idaho's four-
year Universities.
Please direct any questions regarding this report to Randy Gnaedinger at [phone] or myself
at 509-495-4975.
Gervais
Senior Manager, Regulatory Policy
Avista Utilities
509-495-4975
linda. gervais@avi stacorp. com
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AVISTA UTILITIES
SELECTED RESEARCH AND DEVELOPMENT
EFFICENCY PROIECTS . IDAHO
Annual Report
March 29,20t9
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Avista Research and Development Projects Annual Report
March 29, 2019
THE FOLLOWING REPORT WAS
PREPARED IN CONFORMANGE WITH
TDAHO PUBLIC UTTLTTTES COMMTSSTON (tpUC)
CASE NO. AVU-E.13.08
oRDER NO. 32918
March 29,2019
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Avista Research and Development Projects Annual Reporl
March 29, 2019
ANNUAL REPORT
SELECTED RESEARCH AND DEVELOPMENT EFFICENCY PROJECTS
IPUC CASE NO. 32918
TABLE OF CONTENTS
SCOPE OF WORK,..A. lntroduction
B. BackgroundII. KEY EVENTS
A. Request for Proposal
Selection of Projects
Description of Selected Projects
Project Manager and Related Comm unications..............
Agreements
Project Milestones...
ACCOUNTING
Schedule 91 Available Funds...........
Funds Authorized for R&D Projects in 201712018
Funds Expended and Remaining Balance..
Cost-Recovery
.3
.3
.4
.4
.4
.5
.5
B.
c.
D.
E.
F.
A.
B.
c.
D.
A.
B.
c.
D.
IV
7
8
8
PROJECT BENEFITS..
10
10
10
11
71
12
12
72
72
72
13
13
15
Residential Static VAR Compensator (RSVC) Year 4
Aerogel lnsulation System: An lnnovative Energy Efficient Thermal Wall (Phase 1) ..........
lntegrated Design Lab (lDL): Efficiency Based on Operative Temperatures........................
IDL Energy Management Phase 2V. RESEARCH IN.PROGRESS................A. Summary of Research ln-Progress
B. Other Relevant Activity
LIST OF APPENDICES
APPENDIX A
APPENDIX B
APPENDIX C
APPENDIX D
APPENDIX E
APPENDIX F
APPENDIX G
APPENDIX H
APPENDIX I
APPENDIX J
APPENDIX K
APPENDIX L
Two-Page Reports
Request for lnterest
Boise State University Agreement
University of ldaho Agreements
Final Report: RSVC Year 4
Final Report: Aerogel Phase 1
Final Report: IDL Operative Temperatures
Final Report: Robust Microgrid
Two-Page Report:Aerogel Phase 2
Two.Page Report: IDL lR Camera
Two-Page Report: All-lron Battery
Two-Page Report: Energy Trading System
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Avista Research and Development Projects Annual Report
March 29,2019
I. SCOPE OF WORK
A. lntroduction
This report is prepared in conformance with ldaho Public Utilities Commission
(IPUC) order No 32918. This includes key events during the reporting period and
accounting for related expend itu res.
Avista Corporation, doing business as Avista Utilities (hereinafter Avista or
Company), at 1411 East Mission Avenue, Spokane, Washington, is an energy
company involved in the production, transmission and distribution of energy as well
as other energy-related businesses. Avista Utilities is the operating division that
provides electric service to more than 600,000 electric and natural gas customers.
Their service territory covers 30,000 square miles in eastern Washington, northern
ldaho and parts of southern and eastern Oregon, with a population of 1.5 million.
Avista also provides retail electric service in Juneau, AK through a subsidiary called
Alaska Electric Light and Power Company.
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On August 30, 2013 Avista applied for an order authorizing it to accumulate and
account for customer revenues that will provide funding for selected electric energy
efficiency research and development (R&D) projects, proposed and implemented
by the state of ldaho's four-year Universities. On October 31, 2013 Order No.
32918 was granted to Avista. Avista now recovers up to $300,000 per year of
revenue to research from the Company's Schedule 91 Energy Efficiency Rider
tariff.
This program provides a stable base of research and development funding that
allows research institutions to sustain quality research programs that benefit
customers. lt is also consistent with the former ldaho Governor's Global
Entrepreneurial Mission "iGem" initiative in which industry would provide R&D
funding to supplement funding provided by the State of ldaho.
B. Background
ln the 1990s, with the prospect of electric deregulation, utilities reduced or
eliminated budgets that would increase costs not included by third-party marketers
for sales of power to end-users. Research and development was one of those
costs. This has led to the utility industry having the lowest R&D share of net sales
among all US industries.
Research and development is defined as applied R&D that could yield benefits to
customers in the next one to four years.
ln 2010, the former Governor announced Idaho would support university research
as a policy initiative with some funding provided by the state and supplemental
funding expected from other sources. This project provides additional funding to
selected research.
II. KEY EVENTS
A. Request for Proposal
The Request for Proposal (RFP) for projects funded in 201712018 academic year
was prepared and distributed to all three ldaho Universities in March 2017. A full
copy of the RFP is included in Appendix B.
On April 21,2017, Avista received 10 proposals from the University of ldaho, 1
proposal from Boise State University, and 4 proposals from ldaho State University.
Following is a list of the proposals received:
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Avista Research and Development Projects Annual Report
Itlarch 29 2019
Universitv of ldaho
1. Proof of Concept All-lron Battery with Carbon Electrodes
2. Data lnfluenced Reduced-Order Virtual Commissioning
3. Replacing Standard Water Heaters with Heat Pump Water Heaters Proposal
4. Aerogel lnsulation System: An lnnovative Energy Efficient ThermalWall
5. Plug and Play Solar Energy for Any House
6. Grid-Tie lnverter Reactive Power Production
7. Robust Microgrid for Downtown Spokane
8. Energy Trading System
9. Continuation of CAES Water/Energy Conservation Analysis with Avista
10. Managing for Efficiency Based on Operative Temperatures
Boise State Universitv
1. A Demand-Side Approach to Conservation by Voltage Regulation Enabled
by Residential Static Var Compensators
ldaho State Universitv
1. Cyber Security and Resilience Proposal
2. lmprovements in Electrical Grid Reliability and Efficiency3. Grid Stability Proposal
4. Smart Meter Messaging for Customer Driven Conservation
B. Selection of Projects
Avista prepared an evaluation matrix for the 15 proposed projects. A team of
individuals representing Distribution, Transmission Planning, Generation and
Demand Side Management, co-filled out the matrix to rank each of the projects.
The following criteria in no particular order were considered in the ranking process.
. Research Areas Already Being Done (EPRI, WSU, AVA)
Com plemenURedundanUNew. PotentialValue to Customers kwh/KW$ (1-10). COz Emission Reduction (Y/N). Market Potential (1-10)o Are Results Measurable (Y/N). Aligned with Avista Business Functions (Y/N). New or Novel (Y/N). Ranking (1 -10)
C. Description of Selected Projects
Following is a brief description of each of the four selected projects from 201712018
academic year. Project teams compiled "Two-Page Reports" which summarize and
highlight project details. These Two-Page Reports are included in Appendix A.
Additional details are included in the final project reports in Appendix E, Appendix
F, Appendix G, and Appendix H.
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Avista Research and Development Projects Annual Report
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RSVC Year 4: A Demand-Side App to Conservation bv Voltaoe Reoulation
Enabled bv Residential Static VAR Compensators (RSVCS)
Summary of Pass Progress (Years 1-3)
Phase I of this project was funded in Year 1 and consisted of a study model of a
Residential Static VAR Compensator (RSVC) for regulating residential voltages.
Phase 1 showed that a single-phase RSVC offers a significant potential for energy
savings by voltage regulation and can become a valuable tool in energy
conservation programs, especially during peak demand hours.
Phase ll of this project was completed without funding assistance from Avista. This
phase consisted of building an open loop control prototype of the RSVC device.
The implementation strategy involved a software centered approach that used a
FPGA in conjunction with bidirectional switches. The bidirectional switches were
constructed using unidirectional devices (lGBTs) and diodes and controlled using a
state machine to provide a smooth transition between states.
Phase lll of this project was funded in Year 2 and consisted of performing a time-
series simulation over multiple months using a model developed in OpenDSS of
downtown Spokane and a rural feeder near Lake Pend Oreille. The simulations
showed that the deployment of RSVCs could enhance conservation by voltage
regulation (CVR) by flattening the voltage profile along the feeder.
The objectives of the research during Phase lV (Year 3) were to develop the
framework and simulation platforms to allow for distributed control algorithm tests of
the RSVC. The research included simulation of 1) voltage control,2) powerfactor
control, 3) multi-RSVC interaction, 4) RSVC interaction with voltage regulators,
battery energy storage systems, photovoltaic generation, and pre-existing capacitor
banks, 5) conservation by voltage reduction, and 6) RSVC simulation comparison to
field measurement data.
Project Description for Year 4
The overall goal of the RSVC project during Year 4 was to simulate, design, and
implement a laboratory prototype of a RSVC equipped with two automatic control
loops for customer load voltage regulation and minimum load power consumption.
The faster voltage regulation control loop regulates the customer load voltage to
any desired reference voltage within Range A of ANSI C84.1 (120 V nominal plus
or minus 5%) and a secondary slower control loop adjusts the reference voltage to
track the point of minimum power consumption by the customer load. This is a new
approach to CVR which is tailored to the nature of the customer load, which may
decrease or increase its energy consumption under a reduced voltage. This
demand-side approach to CVR is a radical departure from current strategies which
have been in existence for over 30 years but have not been widely adopted by
electric utilities due to high costs and technical challenges.
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Avista Research and Development Projects Annual Report
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Aerroqel lnsulation Svstem: An lnnovative Enerqy Efficient Thermal Wall (Phase 1)
ln 2015, about 40o/o of the total U.S. energy consumption was consumed in
residential and commercial buildings, and the government promotes renovation of
existing buildings to meet minimum energy performance requirements. The main
objective of this project was to investigate the efficiency of Aerogel insulation
blankets as a new insulation material for residential buildings. The research tasks
were conducted using field measurements and computer simulations. The field
measurements were collected from a real apartment where walls were insulated
with the Aerogel blankets. ln parallel, a computational fluid dynamic (CFD) code
was developed to validate the field data and perform additional key parameters.
lnteqrated Desiqn Lab (lDL): Efficiencv Based on Operative Temperatures
The objectives of the project were to profile typical thermostat setpoints found in
operation, test alternative control methods, and estimate potential savings. This
study, based on extensive data collection paired with energy modeling, provided
key insights on how to best balance thermal comfort and energy savings for small
commercial office buildings in the Pacific Northwest. This research provided critical
data to determine how effective an operative temperature strategy impacted both
energy use and occupant comfort. The research leveraged data analytics, energy
modeling, and comfort standards to inform efficient control schemes that both save
energy and ensure comfort.
Framework for Sitinq and Sizinq Enerqv Storaqe for Enhanced Performance of the
Avista Svstem
The objective of this project was to develop and trialtest a Distribution Resources
Plan (DRP) appropriate for the northern region of ldaho. The DRP included
methods for integration capacity analysis (lCA) and locational net benefits analysis
(LNBA). These analyses, respectively, determined how many distributed energy
resources (DER) the system can handle and how the value of those DERs are
calculated. To test these methods, a section of interest of the Avista utility grid was
modeled in GridLAB-D. After this model was verified, the lCA and LNBA methods
were applied.
D. Project Manager and Related Communications
Avista set out to find an independent third-party project manager based in ldaho.
On September 26, 2014 Avista entered into an agreement with T-O Engineers as
this independent third-party project manager. T-O Engineers is a company based in
ldaho, with offices in Boise, Coeur d'Alene, Meridian and Nampa, ldaho, as well as
Cody, Wyoming, Heber City, Utah, and Spokane, Washington.
T-O is tasked with providing project management, organizational structure,
milestone setup, milestone tracking, and incidental administrative services. The
project manager for T-O Engineers is JR Norvell, PE and the deputy project
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Avista Research and Development Projects Annual Report
March 29, 2019
manager is Natasha Jostad, PE. JR and Natasha are based out of the Coeur
d'Alene and Spokane offices, respectively.
E. Agreements
On September 1,2017 Avista entered into an agreement with Boise State
University. The full agreement is included as Appendix C.
By July 27,2017 Avista executed individual task orders for each of the University of
ldaho research projects selected. The agreements are included in Appendix D.
F. Project Milestones
The following graphics identify the overall research and development milestones, as
well as the milestones for each p@ect. Final reports from each Principle
lnvestigator were submitted in the fall of 2018.1n addition to the written report, each
research team presented their findings in person to Avista. The IDL and Robust
Microgrid teams both presented their findings to Avista on August 16,2018, and the
RSVC and Aerogel teams presented their findings on August 17,2018.
Fa!] Seinecter Sorlnq Semo3ter Summer Somoator
l. ProJect Klcltofl I
2. Follow on Proporal lo Avlstt r
3. Final Report and P?e6entation to
Avlsta I
a. IPUC Dcliv.rablct I
Milestones/Deliverables All Projects
Tark Ducrigtion Sql17 QclllT Nov,17 D!cr17 JmrrE F.btlt Hrrfia Apt lS lihyflt Junltt JuUf t AugltE
Fall Semester Sprlnq Somesto.Summar Semerter
Task 1: Design & Simulstion of Voltage
Requlation Looo
Task 2: Oeeign & Simulation of Power
Regulation Loop
f.rk 3.: Opcn-Loop Prolotypc Bulldlrg
O T*llng at 60 V
Ta3k 3b: Volt gG Rcgul.Uon llcrlgn E
Tcrtlng
Taik 3c: Power Ragulation De3ign &
Tcrtlng
Tark 4: Testing & Vslidation
Task 5: Stage Gate teeling
Task 5a: Finsl Pr€Benlrtion
Taak 6: Final Reporl
$rpl17 tu/17 ilovrl7 O.crl7 Jil/t$ Fcb{rt Hrr/t* Ap/18 lltrylii Junltl JulIlE Augng
I I IIIIrIII
Tadr Docripfion
RSVC
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Avista Research and Development Projects Annual Report
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F.ll Scmcrlcr
Tr3l 1: Lltefrturo Survry
Task 2: Aerogel Charastcrizstion and
Acouirino Cornmercial Producti
TerI 3: Fleld Deta Collrcllon
T.rI a: llodollng end Slmul.Uon
Tr3l 5: Co3t Analyrir
TasI 6: Environmontrl lmpact and Final
Roport
Aerogel Phase 1
Tr*t D$erlption €.p,17 Ocr{? l{ovll? Drc,ltT JrnllS Frbll8 llrillt irrttt f,aylt0 JunI'|8 JuUlt Aut/lt
Summer
Task 2: Develop modsls to, 6ites
Taak 3: Collect data foi hoatng
Ts3k il: Conlnrt Pailo,rmlnce vs.
ASHRAE 55
T.rk 5: Esdmete SavlngB (heatingl
Task 6: Collecl dalr toi coollng
Tash 7: Conlrael Pedormanca vB.
ASHRAE 55
Task 8: E3tlm.t. S.vlng3 (coolingl
Taak 9: Develop UYoriflow tor
Practition€rE
8ryfi? Oafl? Novil7 D.dl7 Jenllt Fr!flt tlrrfit tfrrlt ll yrl8 Jurftt Julrr8 AoilltT.!k D.ier$don
Fall Semester
T*k t: Locatlon Value Analyalt
Tark 2: Dlrtrlbutad rasorrrca plens
T.Bk 3: Non-wlr. 3olutlont
fark 4: Fln., Rcport
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Task 1: Select Siles
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Avista Research and Development Projects Annual Report
March 29, 2019
I!!. ACCOUNTING
A. Schedule 91 Available Funds
Effective November 1,2013, Avista can fund up to $300,000 per year of R&D from
revenue collected through Avista's Schedule 91, Energy Efficiency Rider
Adjustment. At the end of each year, any monies not allocated toward payment on
R&D projects roll over as available resources for the next year. A summary of the
balance for Schedule 91 from the beginning of Order No. 32918 is shown in the
table below.
B. Funds Authorized for R&D Projects in20'1712018
Contracts for 201712018 are as follows:
Academic
Year
New
Funding
Balance
from
Previous
Year
Total
Funds
Available
Contracted
Amount
Actual
Expenditures Balance
2014t2015 $300,000.00 $0.00 $300,000.00 $287,941.00 $243,467.32 $56,532.68
2015t2016 $300,000.00 $56,532.68 $356,532.68 $252,493.00 $235,809.03 $120,723.65
201612017 $300,000.00 $120,723.65 $420,723.6s $372,66s.16 $358,641.82 $62,081.8s
2017t2018 $300,000.00 $62,081.83 $362,081.83 $317,074.89 $313,358.82 $48,723.01
2018t2019 $300,000.00 $48,723.01 $348,723.01 $299,463.00
Agency Description Contract
Amount Point of Contact
Boise State University RSVC Year 4 $ 90,574.00 Dr. Said Ahmed-Zaid
University of ldaho Aerogel Phase 1 $ 88,777.00 Dr. Ahmed lbrahim
University of ldaho Operative Tem peratures $ 24,011.00 Elizabeth Cooper
University of ldaho Robust Microgrid $ 83,712.89 Dr. Herbert L. Hess
T-O Engineers Project Manager $ 30,000.00 James R. Norvell
Total $ 317,074.89
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C. Funds Expended and Remaining Balance
Following is the final budget summary for 201712018 FY R&D Projects
D. Cost-Recovery
The costs associated with R&D are funded from revenue collected through Avista's
Schedule 91 - Energy Efficiency Rider Adjustment. The outstanding balance was
rolled over to the current year's R&D budget, as seen in the table in Section Ill A.
All R&D projects are invoiced on a time and materials basis with an amount not to
exceed. The costs would be included in Avista's annual tariff filing in June if the
rider balance requires a true-up.
Agency Description Contract
Amount
Total
Expended
Budget
Remaining
Boise State University RSVC Year 4 $ 90,574.00 $ 90,376.63 $ 197.37
University of ldaho Aerogel Phase 1 $ 88,777.00 $ 87,710.49 $ 1,066.51
University of ldaho Operative Tem peratures $ 24,011.00 $ 23,610.26 $ 400.74
University of ldaho Robust Microgrid $ 83,712.89 $ 81,661.44 $ 2,051.45
T-O Engineers Project Manager $ 30,000.00 $ 30,000.00 $ 0.00
Totals $ 317,074.89 $ 313,358.82 $ 3,671.22
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Avista Research and Development Projects Annual Report
l\tatah ?Q ,O1Q
IV. PROJECT BENEFITS
A. Residential Static VAR Compensator (RSVC) Year 4
The proposed RSVC has several advantages compared to a conventional thyristor-
fired SVC which include an almost sinusoidal inductor current, sub-cycle reactive
power controllability as opposed to half-cycle controllability, lower footprint for
reactive components, and the feasibility of building a single-phase voltage
regulation device. RSVC has a wide range of applications for utilities and
customers. These applications include voltage regulation, Conservation by Voltage
Reduction (CVR), optimum power point tracking and minimizing the voltage
transients during fixing capacitors in the distribution systems. These applications
result in cost savings for electric utilities especially during peak demand hours.
B. Aerogel lnsulation System: An lnnovative Energy Efficient Thermal Wall
(Phase 1)
Energy sustainability is a crucial issue for humanity's development in modern era,
which can significantly impact future quality of life and the environment. The
industry is moving towards the construction of sustainable, energy efficient
buildings. The outcomes of the research will be applied to help Avista customers
save energy, reducing the need for natural gas and electricity. The Aerogel blankets
will potentially be used in retrofitting existing structures to improve efficiency and as
a new well-developed material for new construction.
C. lntegrated Design Lab (lDL): Efficiency Based on Operative Temperatures
The incentive for this study was based on the effect surface temperatures have on
comfort. The research team found that by incorporating the surface temperatures to
develop holistic comfort metrics, the air temperature thermostat setpoints could be
changed to increase the comfort of office employees in the Pacific Northwest. This
simple change resulted in significant savings and other studies suggest that it would
also increase employee happiness, wellbeing, and productivity. At the very least,
engineers, controls manufacturers, and building managers should re-visit the
default heating and cooling setpoints of 70 -74 of that are currently in place in most
offices.
D. IDL Energy Management Phase 2
The software products created in this project, when refined for manufacture, may be
packaged, and sold. While planning software may be sold, the underlying open
source applications are available at little or no cost. This open source concept
makes the software products economically attractive. There is an industry need for
such planning software at a competitive price. There is value in providing such
plug-and-play software, value that companies, including utilities, are willing to pay
for. The open source nature of the software presents the opportunity for individual
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Avista Research and Development Projects Annual Report
March 29,2019
users to not only suggest ideas on what might change within the software but to
tailor the software as desired.
V. RESEARCHIN.PROGRESS
A. Summary of Research ln-Progress
There are currently four projects in progress for the 201812019 academic year.
Project kick-off meetings were held on-site at each University of ldaho location in
early fall 2018. Two stage gate meetings will be held throughout the academic year
where the teams have an opportunity to showcase their research and plan
upcoming work with input from Avista. Two-Page Reports were prepared in the
spring of 2019 and describe the project objectives, business value and industry
need. Additionally, the individual project tasks are summarized. Two-Page Reports
are included in Appendices ! through L. Each team will present their research and
findings to Avista in the fall of 2019, as well as prepare a final research report. Final
reports will be filed with the 2020 Annual Report.
The individual project tasks for the current IPUC funding projects are presented
below.
fask 2: Aerogel window samples acqulsition
fask 3: Computer vatidatlon of Aerogol+ased
glazing
Task 5: Energy simulalion for annual savings
Tas* 6: Cost analysis
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Aerorel Phase 2
T.sl thrcription 5ep/rB octltS ilov/18 Dec/18 tanl19 Febh9 MailLg Apiltg M.y/19 lunl19 tulh9 Augr/l9
fask 4: Simulation of single-family houso
Avista Research and Development Projects Annual Report
March 29. 2019
tall SeDeste.
fask I ; Proiect planning/.eporting
Ta3k 2: Latoraturs Review
Tesk 3: Deploy lR camera in chamber
Task 4: Collect operational data
Task 5: Develop algorithm to process
measuioments
Task 6: Translab lR files
Task 7: Estimato savings
Task E: Develop Workflow for Practitiooers
Summea Semeste,
fask 1: Collect flnal data on 20 ml cell
fask 2: Construct 200 ml cell
fask 3: Characterize 200 ml cell
fa3k 4: Prepare tollow-up proposal
Iask 5: Build 'lL battery
Task 6: Charactorizo and prosent lL cell
All-lron Battery
Task D€scription S€pllt Oct/18 ilov/l8 Dec/18 tznh9 Feb/lg Maillg Aprll9 May/19 Jun/19 fuJl,g Augltg
Fall s€rerter
Task 2: Dasign and model the system
fask 3: Develop the dalabase architecture
and schema and seloct a DBirS.
fask 4: Analyzo sacurity risks and dssign and
lmplement securlty mechanisms
fask 5: Develop a simulated modol of the
fask 6: Design and sketch Web andlor App
lntorfaces: User and Administration
fask 7: Bulld the prototype software
Task E: lntegrate the t.ansaction conlrol
system with the dislribution model
fask 9: Design and porform tosts tor:
Functlonallty, Usabllity, and Security
Iask 10: Produca u3or and administrator
usage guides
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IDL - lR Camera
Task Detcription 5€p/18 OctllS Hov/18 oecllt lanl19 teb/t9 Marl19 N.he May/19 Jun/19 tuu19 Aug/19
Task D€sc.lption Sep/18 OcVlS l{ovl18 Dec/18 lanh9 feb/19 Mar/19 Apt/1g Mey/19 ltnh9 lullL9 Aus/l9
SemeSler e,
Iask 1; ileet with Avista
Avista Research and Development Projects Annual Report
March 29,2019
B. Other Relevant Activity
A progress meeting is held bi-monthly for each project. These meetings typically
take 0.5 hours and include a review of schedule, bi-monthly progress reporting,
invoicing, Avista comments, and action items for the next meeting. The meetings
are organized and led by the lndependent Program Manager, T-O Engineers.
Attendees for each meeting include the Principal lnvestigator, Co-lnvestigators,
Student Researchers, Avista personnel, and the lndependent Program Manager.
Contracts for these projects total $299,463.00 and are summarized below
Funds expended, and additional budget details will be summarized in the 2020
Annual Report.
Agency Description Contract
Amount Point of Contact
University of ldaho Aerogel Phase 2 $ 82,873.00 Dr. Ahmed lbrahim
University of ldaho lR Camera $ 48,678.00 Kenneth Baker &
Dr. Damon Woods
University of ldaho All-lron Battery $ 48,141.00 Dr. Peter Allen
University of ldaho Energy Trading System $ 89,771.00 Dr. Yacine Chakhchoukh
T-O Engineers Project Manager $ 30,000.00 James R. Norvell
Tota!$ 299,463.00
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APPENDIX A
Two-Page Reports
*tnsrn X
B AEwsrfrBO!SE STATE UNIVENSITY
A DEMAND.SIDE APPROACH TO CONSERVATION BY
VOLTAGE REGUIATION ENABLED BY RESIDENTIAL
STATIC vAR COMPENSATORS (RSvCs)
Project Duration: September 2017 - August 2018 Project Cost: Total Funding $90,574
OBJEGTIVE
The overall goal of the RSVC project during
Year IV is to simulate, design, and implement
a laboratory prototype of a Residential Static
VAR Compensator (RSVC) equipped with two
automatic control loops for customer load
voltage regulation and minimum load power
consumption. The faster voltage regulation
control loop regulates the customer load
voltage to any desired reference voltage within
Range A of ANSI C84.1 (120 V nominal plus or
minus 5olo) and a secondary slower control
loop adjusts the reference voltage to track the
point of minimum power consumption by the
customer load. This is a new approach to
conservation by voltage regulation (CVR)
which is tailored to the nature of the customer
load, which may decrease or increase its
energy consumption under a reduced voltage.
This demand-side approach to CVR is a radical
departure from current strategies which have
been in existence for over 30 years but have
not been widely adopted by electric utilities
due to high costs and technical challenges.
BUSINESS VALUE
The deployment of multiple RSVCs offers a
cost-effective method for energy savings by
applying conservation by voltage regulation
during peak demand hours. It can become a
valuable tool in a utility energy efficiency and
demand-side management programs.
INDUSTRY NEED AND BACKGROUND
The new single-phase RSVC device has a
distinct advantage over a conventional shunt
capacitor of being able to operate in a
capacitive or inductive mode without
generating substantial harmonics. This RSVC
employs a pulse-width-modulation (PWM)
technique applied to two specially-designed
bidirectional switches controlling the variable
reactive power output. This flexible device can
be used in multiple applications such as
continuous voltage control at a load point,
power factor control, mitigation of power
quality issues, etc. The new RSVC device is a
competitive device on several fronts including
cost, footprint, and smart-grid applicability or
compatibility. Figure 1 shows the prototype of
the open-loop RSVC developed during previous
phases of the project. Several relevant studies
were carried out to study of the operation of
an RSVC for regulating a residential voltage
and to study the potential benefits of deploying
multiple RSVCs on the residential side of
d istri bution networks.
Transformer Output
Voltage
Figure l: Simulation Model for RSVC
PROJEGT TASKS - Year lV
Project Management
Internal weekly project coordination meetings
take place every Wednesday morning. Bi-
weekly status meetings with Avista are
scheduled on Thursdays.
Task 1: Voltage Regulation Loop Design
The objective of this task is to design and
implement the voltage regulation loop for an
RSVC using MATLAB/Simulink models. This
control loop regulates the residential voltage
by changing the reactive power provided by a
PWM-based switched inductor. Figure 2 shows
a top-level block diagram for both control
loops.
6
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Voltsge
Switch
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Csvc
swt
Based
Bidirecliooal
Switch
Switched
Inductor
Figure 2: RSVC Voltage and Power Regulation Loops
Task 2: Power Regulation Loop Design
The RSVC power regulation loop is designed as
a slower control loop than the inner voltage
control loop to build an inherent time
decoupling between the two control loops and
to avoid a possible loop interaction. This task
consists of designing a minimum power point
algorithm (derived from maximum power point
tracker available in the literature) that will
track the power consumed by the residential
customers with the objective of reducing the
customer power. Simulation results for the two
control loops show that the output power for a
2 kW resistive load can be reduced 1.8 kW by
reducing the residential voltage from 120 tolL4 V. Figure 3 below shows the power
consumption reduced as a result of decreasing
the voltage.
Control
prototype consisted of a 190-pF capacitor anda 30-mH inductor choke. Preliminary test
results were compiled at 60 VAC with a 20-ohm
resistive load. The switching frequency for the
switches was varied between 3 kHz and 12
kHz. Table 1 shows the RSVC output voltage
(Vo) and RSVC power losses (PL) as a result of
varying the duty cycle at discrete frequencies,
Table l: Hardware Prototype Results
In the next phase of hardware development,the voltage regulation loop will be
implemented using a voltage transducer
measuring a replica of the RSVC voltage which
is also the customer load voltage. The power
loop will require the same voltage transducer
as well as a current transducer monitoring the
customer load current. The two transducer
outputs will allow the computation of the
average power consumed by the load.
Task 4: Testing of an RSVC prototype in a
laboratory or home environment
These tasks are ongoing.
PROJECT TEAM
SGHEDULE
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Figure 3: Minimum power point tracking with 2 kW
residential load (work in progress)
Task 3: Design of a Functional Laboratory
Prototype of an RSVC
An RSVC prototype is being developed in a
power laboratory at Boise State University.
This prototype is based on the simulation
model shown in Figure 1. The device can
regulate a residential load voltage with a fixed
capacitor in shunt with a reactor controlled by
two bidirectional switches. The two switches
are controlled in a complementary mannerusing a pulse-width-modulation (PWM)
technique that allows the reactor to function asa continuously-variable inductor. An early
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3 75.4 9 72.4 t7 70.7 22 58 19
6 75.4 9 72.5 18 70.8 20 58 19
9 75.4 9 72.5 19 70.6 27 58 19
L2 75.4 9 72.4 22 70.8 29 58 19
PRIXGIPAL INVESTIGATORS
Name Dr. Said Ahmed-Zaid
Oroanization Boise State Universitv
Email sah medzaid@boisestate. edu
Name Dr. lohn Stubban
Orqanization Boise State UniversiW
Email iohnstu bban (o boisestate.ed u
RESEARCH ASSISTAIITS
Name Muhammad Kamran Latif
Orqanization Boise State University
Email mu hammad latif(A u. boisestate. edu
Name Zivano Liano
Oroanization Boise State Universitv
Email ziva no liano @ u. boisestate.edu
TASX TITE
ALLOGATED
START
DATE
Ftl{lsH
DATE
Task 1 3 month Sep'17 Oct'17
Task 2 4 months Nov'17 Dec'17
Task 3 1 month Sep'17 May'18
Task 4 2 months .lun'18 Auo'18
Task 5 2 months lulv'18 Auo'18
The information contalned in this documenl is proprietary and confidential
L@p
Universityotldaho AH-sETA
College of Engineering
Aerogel Insulation System: An Innovative Energy
Efficient Thermal Wall
Project Duration: 12 months Project Cost: Total Funding $88,777
OBJEGTIVE
In 2015, about 4Oo/o of the total U.S. energy
consumption was consumed in residential and
commercial buildings, and the government
promotes renovation of existing buildings tomeet minimum energy performance
requirements. The main objective of thisproject is to investigate the efficiency of
Aerogel insulation blankets as a new
insulation material for residential buildings.
The research tasks are conducted using field
measurements and computer simulations.
The field measurements are being collected
from a real apartment where walls were
insulated with the Aerogel blankets. In
parallel, a computational fluid dynamic (CFD)
code is developed to validate the field data
and perform additional key parameters.
BUSINESS VALUE
It is anticipated that the use of Aerogel
reduces the heat transfer across building
envelopes and therefore will reduce the
annual heat loss by 50o/o compared to the
currently used insulation material(s). In
addition, a life cycle cost analysis with a full
consideration of service life-cost will be
performed and compared to the performance
of conventional insulation materials.
INDUSTRY NEED
Energy sustainability is a crucial issue for the
humanity's development in modern era,
which can significantly impact future quality
of life and the environment. The industry ismoving towards the construction of
sustainable-energy efficient buildings. The
outcomes of the current research will be
applied to help Avista customers save energy,
reducing need for natural gas and electricity.
The Aerogel blankets will be efficiently used in
retrofitting existing structures.
BAGKGROUND
Aerogel, also called solid smoke, is a
synthetic porous material with remarkable
properties. Aerogels are dried gels with a very
high porosity. It was discovered in the early
1930s. Aerogel molecules do not decomposeat high temperatures and do not release
harmful gases. Even at 800oC, the thermal
conductivity of Aerogel is only 43 mW/(m. K).More information could be found in
https ://www. aerooel,com/ resources/commo
n / u se rf i I es/f i I e/ D a ta o/o 2 0 S h e etVSpa qe I oft :
Eu ropean- Datasheet-EN. pdf
SGOPE
Acceptable insulation materials need to
achieve as low thermal conductivity as
possible, enabling a high thermal resistance
as well as a low thermal transmittance. The
scope of this project is mainly focused on
evaluating the ability of the Aerogel blanketsto save energy through a comprehensive
study which is broken down as follows:
Task 1: Literature Survey
Various studies have reported on the
characterization of Aerogel, along withpreliminary investigation of its
implementation as a super insulator,
(Somana 2012, Huang 2OL2, Neugebauer
2OO4, and New York State of Energy 2OL3).
Task 2: Aerogel Acquisition
The team has purchased 800 ft2 of the
Aerogel blankets. The commercial product
name is Spaceloft. It has a 10mm thickness,
and it was delivered as a roll. The team also
purchased a Campbell Scientific data logger,
thermocouples and two heat flux sensors to
collect data from walls insulated by the
Aerogel with other needed supplies.
Task 3: Field Data Collection
Dr. Ibrahim and his team has started field
data collection. Thirty thermocouple sensors
have been placed in one room of the
apartment. Sensors have been mounted on
all walls in the room to record data with
existing insulation and with Aerogel. Figure 1
shows the thermocouples attached to two
walls of the room, while Figure 2 shows
Temperature vs. time for the south wall
(without Aerogel). The Team built a cubical
frame with all walls made from a pure
Aerogel. The temperatures at multiple
locations across the box were measured and
will be used to verify the computer
simulations.
Task 4: Modeling and Simulation
Dr. Tao Xing, his Postdoctoral Fellow Dr.
Rabijit Dutta, and his graduate student are
using computational fluid dynamics (CFD) to
simulate a square box built using the Aerogel
and are using EnergyPlus to simulate the
apartment under test. The purpose of using
CFD is to determine the heat conductivity of
the Aerogel by comparing the predicted inner
wall temperature with the measurements.
Figure 3 shows the preliminary comparison.
Ongoing work includes trying different mesh
resolutions, boundary conditions, and wall
models. Once heat conductivity of the Aerogel
is determined, the value will be used for
apartment simulations using EnergyPlus.
Figure l: Interior view of apartment thermocouplel
Task 6: Environmental lmpact
This task will be performed after task 4
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Figure 3: Comparison between the predicted inner wall
temperature using CFD and experimental measurements
for a square Aerogel box.
DELIVERABLES
The main deliverable of this project will be a
final report includes:1. All the needed information regarding the
field data collection and the computer
simulations, and the exact thermal
conductivity of the Aerogel blankets.2. Cost analysis to compare the existing cost
of the current insulation material(s) with
the anticipated cost of the walls insulated
with the Aerogel.
PROJEGT TEAM
SGHEDULE
o o s(x, 10q) 15(D 2q)O 25q) 3qX)
Tire (*cond5)
Figure 2: Temperature versus time for the south wall
The team is currently working on the Analysis
of the collected data and how that will be
used in the generation of results using the
computer simulation.
Task 5: Cost Analysis
This task will be performed after task 4.
PRr XCTPAL I IfVESTIGATOR(S)
Name Ahmed Ibrahim
Oroanization Universitv of Idaho-Civil Enqineerinq
Contact #208
Email aibrah im@u idaho.edu
Name Tao Xinq
Oroanization University of Idaho-Mechanical Enqineerinq
Contact #208 885 9032
Email [e-mail]
Name Brian Johnson
Orqanization University of Idaho-Electrical Engineering
Contact #208 885 6902
Email b ioh nson @u ida ho. ed u
RESEARGH ASSISTAXTS
Name Moammed Mudaqio
Orqanization Universitv of Idaho-Civil Enqineerinq
Email [e-mail]
Name Shimul Hazra
Orqanization University of Idaho-Mechanical Engineering
Email hazr0186(0va ndals. uidaho.ed u
TASX TIME
AIJ.OCATED
START
DATE
F!1{tSH
DATE
{Task 1: Literature
review){5 Months}{8/2or7}{1/2018}
{Task 2: Material
purchasinq){2 Months}{to/2oL7}{L2/2OL7}
{Task 3: Field Data
Collection){3 Months}{ 1/20 18}{3/2018}
{Task 4: Simulation {9/20t7){4/20t8)
{Task 5: Cost
Analysis){2 Months}{4/2Ot7){6/20 18}
{Task 6: Enviro
ImDact){2 Months}{6/20L7){8/20 18}
The informalion contained in this document is proprietary and confidential.
t
,
a
1
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I
3
Universityoyldaho
Cotlege of Art and Architecture
Efficiency Based on Operative Temperatures
Project Duration: 12 months Project Cost: Total Funding $24,011
AYrstsrfi
OBJECTIVE
The outline of the work is to profile typical
thermostat setpoints found in operation, test
alternative control methods, and estimate
potential savings. This study, based on
extensive data collection paired with energy
modeling, would provide key insights on how
to best balance thermal comfort and energy
savings for small commercial office buildings in
the Pacific Northwest. This research provides
critical data to determine how effective an
operative temperature strategy might impact
both energy use and occupant comfort. The
research leverages data analytics, energy
modeling, and comfort standards to inform
efficient control schemes that both save
energy and ensure comfort.
BUSINESS VALUE
Operative temperature control would allow for
wider air temperature setpoints, thus saving
energy each year. Increasing the cooling
setpoint by 5oF has been shown to reduce total
HVAC energy by 27o/o. The adoption of
operative thermostats could result in
widespread energy savings and dramatically
enhance occupant comfort, thus making it an
attractive service to offer to clients.
INDUSTRY NEED
Most buildings manage their heating or cooling
based solely on zone air temperature. Even
when the thermostats are kept within a narrow
band of 4oF, occupant complaints persist
(Arens, et al., 2010). A large factor of human
comfort is being missed in conventional
thermostats: the inclusion of the mean radiant
temperature. While operative temperature is
widely used for predicting human comfort,
rarely is it directly used in building controls. A
control system that incorporates the operative
temperature of a zone would allow for a wider
range of supply air temperatures and better
meet the needs of occupants. The wider range
of air temperatures would reduce energy
consumption and help to capitalize on
operational features such as natural
ventilation, night-flush and optimized set-
points.
BAGKGROUND
Many previous studies have established that
the temperatures of the surfaces surrounding
us have a far greater impact on our comfort
than the air temperature (Olesen 2007). A
better comfort metric is the operative
temperature which is a mix of air and surface
temperatures. While operative temperature is
widely used for predicting human comfort,
rarely is it directly used in building controls.
SGOPE
The new strategy will be modeled in annual
EnergyPlus simulations. The EnergyPlus
models will be informed by the temperature
and thermostat data gathered at the site
instead of ideal assumptions. The simulation
results will be used to estimate energy savings
and comfort impacts of incorporating surface
temperatures into thermostat controls. The
goal of the research is to identify the savings
possible by shifting controls from their current
baseline settings to a strategy that is more in
line with the demands of occupant comfoft.
Task 1: Project Planning and Reporting
Conduct team meetings and ongoing project
updates, reports and deliverables as requiredby Avista staff, project management
contractor and the PUC. Ongoing throughout
the project.
Task 2: Establish Baseline Setpoints
The team will conduct a short literature reviewon typical operational setpoints of small
commercial office spaces in practice and will
reach out to controls engineers, consultants,
and building operators in Avista territory to
establish typical thermostat setpoints in
operation.
Task 3: Select Sites
IDL will work with Avista to select several small
commercial office buildings as case studies.
One site in the Avista territory includes
Lewiston Idaho's old city hall, now the public
works office at 2L5 D street, The team will
identify spaces within these selected buildings
for testing.
Task 4: Collect Operational Data
The research team will deploy an array of data
loggers to collect surface and air temperatures
along with humidity levels, The team will work
with the building operators to collect data on
energy consumption and thermostat setpoints
either through EMS recordings or by linking the
building controls to a program like SkySpark
that can catalog this information.
Task 5: Develop Energy Model
IDL will develop a basic energy model for the
spaces selected in EnergyPlus for analysis. This
will follow Task 3 and be in parallel with Task
4.
Task 6: Test Alternative Controls
Using the energy model, IDL will test
thermostat setpoints based on the operative
temperature instead of the air temperature.
This work may begin at the start of the project
for default building models and will be refined
after the completion of Task 5.
Task 7: Estimate Savings
The team will study energy simulation results
comparing the typical settings found in Task 1
against the alternative controls developed in
Task 6.
Task 8: Develop Workflow for
Practitioners
The final task will be a study of the process that
will add to the current literature and promotethis technology service to furthercommercialization techniques. This
documentation will be part of a master's
student's academic work and publication in a
conference or journal will be sought.
DELIVERABLES
. Project team has coordinated with
several building managers and control
personnel to gather current operational
data and setpoints.. Project team has logged surface and air
temperatures to create thermal comfort
profiles of selected spaces based on
ASHRAE 55 criteria.. Project team has created simple
EnergyPlus models to reflect the
geometry and thermal propefties of the
selected spaces.. Project team has tested operative
temperature control schemes on the
energy model and compared the energy
consumption and comfort predictions to
the original thermostat settings.. Project team is able to estimate typical
energy savings for small commercial
office buildings in the Pacific Northwest
and present a replicable work flow witha control scheme that could be
implemented into a case study.
PROJECT TEAM
SGHEDULE
PRTXCIPAL t1{VESTIGATOR(S)
Name Elizabeth CooDer
Orqanization Universitv of Idaho Inteqrated Desiqn Lab
Contact #(208\ 40t-o644
Email ecoooer@ uida ho.ed u
RESEARCH ASSISTANTS
Name Damon Woods
Oroanization ljniversitv of Idaho Inteorated Desion Lab
Email dwoods@ u idaho.ed u
Name Neha Pokhrel
Oroanization Universitv of ldaho Inteorated Desion Lab
Email nookh [e-mail] u
Name Rvker Belnao
Oroanization Universitv of Idaho Inteqrated Desion Lab
Email rbelnao(ou idaho.ed u
TASX T!TE
ALLOCATED
START
DATE
FrilrsH
DATE
Proiect Plannino t2 o8/17
Establish Baseline Stots 2 05/17 07 /r8
Select Sites 2 08/t7 to/L7
Collect Operational Data 7 09/L7 07 /t7
Develoo Enerov Models 6 LO/17 3/18
Test Alternative Controls 4 03/18 07/t8
Estimate Savinqs 3 05/18 07/t8
Develop Workflow 1 07/18 08/18
The information contained in this document is proprietary and confidential.
Universityotldaho AHwsrfr
College of Engineering
Framework for Siting and Sizing Energy Storage for
Enhanced Perforrnance of the Avista System
Project Duration: 12 months Project Cost: $83,712.89
OBJEGTIVE
To develop and trial-test a Distribution
Resources Plan (DRP) appropriate for the
northern region of Idaho. The DRP will include
methods for integration capacity analysis (ICA)
and locational net benefits analysis (LNBA).
These analyses, respectively, determine how
many distributed energy resources (DER) the
system can handle and how the value of those
DERs will be calculated. To test these methods,
a section of interest of the Avista utility grid
will be modeled in GridLAB-D. After this model
is verified, the ICA and LNBA methods will be
applied. Using the results the methods will be
refined.
BUSINESS VALUE
In recent years, DERs such as solar panels
have been seen as a means to reduce electrical
costs to the facility to which it is attached. DER
also reduce power lost during transmission
from a distant power plant. Another class of
DER, energy storage, may be needed to
compensate for non-dispatchable renewable
generation. By solving local power issues, DERcan defer or eliminate costly system
improvement projects.
DRPs help a utility plan and utilize DER
efficiently.
INDUSTRY NEED
Renewable energy has been shaking the utility
industry in the last decade. Solar panels andother renewable resources break the
traditional utility model and are becoming
increasingly popular as a source of "green"
energy as the price drops to within par of
traditional electricity rates. Unlike nuclear
plants and other sources of traditional
generation, most sources of renewable
generation are unable to be dispatched.
Unplanned and haphazard integration of
renewable generation and other DER can put
local system stability at risk. Careful planning
and control will manage the risk that DER bring
so all parties can fully enjoy the benefits. Thus
utilities are motivated to develop policies
regarding DER in a DRP such as an ICA.
BAGKGROUl{D
As the cost of renewable energy has become
increasingly competitive with traditional
sources of energy, utilities are pressured to
include more DER. In order to safely and
efficiently use DER, utilities need to update
their traditional distribution planning processes
to incorporate DER. California's investor owned
utilities (IOUs) have integrated DERs into the
planning process by using DRPs. This
document outlines the companies plan to
measure the system capacity for DER and
possible new economic models to cover this
new service. Such a plan can forestallthe needto upgrade transmission infrastructure by
using a local non-wired solution.
SGOPE
Task 1: Research Existing DRPs
The research into existing DRPs focused on the
DRPs submitted by California IOUs. These
documents were found on the California Public
Utilities Commission (CPUC) webpage. Notes
were taken on the DRPs starting with the one
submitted by San Diego Gas & Electric
(SDG&E). These notes were then compiled and
processed into the Final Research Report. This
research provides a baseline knowledge of the
methods of other utilities who are also solving
the problem of distributed resource planning.
Task 2: Familiarize with Avista Policies
Research Avista's needs and policies to begin
development of a locational net benefits
model. The teams observations were
developed into a Midterm Research Report.
Task 3: Learn GridLAB-D
GridLAB-D is a new power distribution system
simulation and analysis tool. One of its defining
features is its ability to model emerging smart
grid energy technologies. This feature coupled
with its ability to be integrated with a variety
of third-party data management and analysis
tools makes Gridl-AB-D a leading resource for
testing integrated capacity and locational net
benefits analyses.
The team will learn the GridLAB-D program to
prepare for modeling a representative sectionof the Avista system where a non-wires
solution could be applied to solve near-term
challenges. This reduces modeling time after
the target section data is received.
Task 4: GridLAB-D Modeling
The target section data will be received in the
Common Information Model (CIM) format. The
team will convert this data into a GridLAB-D
model.
Task 5: Integrated Capacity Analysis
Once the GridLAB-D model is complete, the
team will implement SDG&E's ICA method.
This method divides the target section's
feeders into zones and then inserts
increasingly greater generation until a
thermal, voltage, or protection limit is violated.
The results of the analysis will be added into
the Final Research Report.
Task 6: Locational Value Pricing
SDG&E's locational net benefits method will be
applied to 3 different locations in the GridLAB-
D model. The pricing for each location can then
be calculated and the results will be compared
and added into the Final Research Repoft.
DELIVERABLES
. Midterm and Final Research Reportso GridLAB-D model of a representative
part of the Avista power system where
a non-wires solution could be applied to
solve near-term challenges. Results of ICA of the GridLAB-D model. Describe options for performing
Integration Capacity Analysis. Describe options for performing
Locational Net Benefits Analysis
PROJEGT TEAM
SGHEDULE
Appendices
A: Midterm Research Report
Schnitker, Maximilian; Flyn, Nicholas;
Alruwaili, Barjas; Chen, Tianyi. Mid-Term
Research Report. First-Term Research
Summary. University of Idaho. ll/27/2017
PRrl{CTPAL TXVESTIGATOR(S)
Name Dr. Herbert Hess
Orqanization University of Idaho
Contact #(208) 88s - 4341
Email h hess@ u ida ho. ed u
Name Dr. Brian Johnson
Orqanization University of Idaho
Contact #(208) 885 - 6902
Email bioh nson@u idaho.ed u
Name Dr. Yacine Chakhchoukh
Oroanization University of Idaho
Contact #(208) 88s - 1550
Email yacinec@u ida ho. edu
RESEARCH ASSISTANTS
Name Jacob Dolan
Oroanization University of Idaho
Email [e-mail]
Name Maximilian Schnitker
Oroanization Universitv of Idaho - Senior Desion
Email schn6884(ova nda ls. uidaho. edu
Name Nicholas Flvnn
Orqanization Universitv of Idaho - Senior Desion
Email Flvn [e-mail]
Name Barias Alruwaili
Orqanization Universitv of Idaho - Senior Desion
Email alru4168@va ndals. uidaho.ed u
Name Tianvi Chen
Orqanization Universaty of Idaho - Senior Desiqn
Email chen [e-mail]
TASX
TITE
ALLOCATED
{# Months}
START
DATE
FllflSH
I'ATE
Research Existino DRPS 4 09/u o1/18
Familiarize with Avista
Policies 2 09/17 rt/17
Learn GridLAB-D 3 rt/t7 02/t8
GridLAB-D Modelinq 2 02/18 04/18
Inteqrated Capacitv Analysis 1 04/L8 05/18
Locational Value Pricinq 2 03/18 0s/18
The information contained in this document is proprietary and confidential.
APPENDIX B
Request for lnterest
fr,,tsrn X
Avista Corporation
East 14l I Mission Ave.Aiivtsrt
wA99202
Request for Proposd (Rtr'P)
Contract No. R-40239
Avista Energy Research (AER) Initiative
INSTRUCTIONS AND REQUIREMENTS
Proposals are due by 4:00 p.m. Pacific Prevailing Time (PPT), April2l,20l7 (the "Due Date")
Avista Corporation is an energy company involved in the production, transmission and distribution of
energy as well as other energy-related businesses. Avista Utilities is the operating division that provides
electric seruice to approximately 3621000 customers and natural gas to approximately 3231000
customers. Avista's selvice territory covers 301000 square miles in eastern Washington, northern Idaho
and parts of southern and eastern Oregon, with a population of 1.5 million. Avista's primary, non-
regulated subsidiary is Ecova. Avista's stock is traded under the ticker symbol 66AVA". For more
information about Avista, visit rvrvw.avistautilities.com.
for
Avista Corporation
East l4l I Mission Ave.
Spokane, WA99202
AYrstsrE
Avista Corporation ("Avista")
RFP Confidentiality Notice
This Request for Proposal ("RFP") may contain information that is marked as confidential and proprietary to
Avista ("Confidential Information" or "Information"). Under no circumstances may the potential Bidder
receiving this RFP use the Confidential Information for any purpose other than to evaluate the requirements of
this RFP and prepare a responsive proposal ("Proposal"). Further, Bidder must limit distribution of the
Information to only those people involved in preparing Bidder's Proposal.
If Bidder determines that they do not wish to submit a Proposal, Bidder must provide a letter to Avista
certifying that they have destroyed the Confidential Information, or return such Information to Avista and
certify in writing that they have not retained any copies or made any unauthorized use or disclosure ofsuch
information.
If Bidder submits a Proposal, a copy of the RFP documents may be retained until Bidder has received notice
of Avista's decision regarding this RFP. If Bidder has not been selected by Avista, Bidder must either return
the Information or destroy such Information and provide a letter to Avista certifying such destruction.
Avista and Bidder will employ the same degree of care with each other's Confidential Information as they use
to protect their own Information and inform their employees of such confidentiality obligations.
RFP No. R-40239 Page 2 of9
Avista Corporation
East l4l I Mission Ave.
Spokane, WA99202
lYvtsrA
Instructions and Requirements
1.0 PURPOSE
in response to the Idaho Public Utilities Commission Order No. 32918, Avista Corporation will fund up to
$300,000 per year ofapplied research that will further promote broad conservation goals ofenergy efficiency
and curtailment. Specifically, Avista is seeking a qualified four year institution in the state of Idaho to
provide such applied research (the "Services"). In light ofthe rapidly changing utility landscape, Avista
would be interested in funding research projects which are forward thinking and would assist the utility in the
development of product and services which provide an energy efficient commodity to its customers. The
applied research and development projects can be one or multiple years and can be used to support university
research programs, facility and studies.
The following institutions are eligible to submit Avista Energy Research (AER) initiative proposals.
l. University of ldaho 2. Boise State University 3. Idaho State University
Persons or institutions submitting a Proposal will be referred to as "Bidder" in this RFP; after execution of a
contract, the Bidder to whom a contract is awarded if any, will be the name of the university ("Institution").
2.0 STATEMENT OF WORK
The attached Statement of Work ("SOW") specifies the activities, deliverables and/or services sought by
Avista. This SOW will be the primary basis for the final SOW to be included under a formal contract, if a
contract is awarded.
3.0 RFP DOCUMENTS
Attached are the following RFP Documents:
. Appendix A - Proposal Cover Sheet
. Appendix B - Sponsored Research and Development Project Agreement
4.0 CONTACTS / SUBMITTALS / SCHEDULE
4.1 All communications with Avista, including questions (see Section 5.1), regarding this RFP must be
directed to Avista's Sole Point of Contact ("SPC"):
Russ Feist
Avista Corporation
l41l East Mission Avenue
PO Box 3727,M5C-33
Spokane, WA99220-3727
Ielephone: (509) 495 -4567
Fax: [phone]
E-Mail: [e-mail]
4.2 Proposals must be received no later than 4:00 PM Pacific Prevailing Time ("PPT"), on April 21,
2017 ("Due Date"). Bidders should submit an electronic copy of their Proposal to
[e-mail]. In addition to an electronic copy, Bidders may also fax their Proposal to 509-
495-8033, or submit a hard copy to the following address:
Avista Corporation
Attn: Greg Yedinak Supply Chain Management (MSC 33)
1411 E. Mission Ave
POBox3727
Spokane, WA 99220-3727
RFP No. R-40239 Page 3 of9
Avista Corporation
East l4l I Mission Ave.
Spokane, WA99202
.#vrsrt
No verbal or telephone Proposals will be considered and Proposals received after the Due Date may
not be evaluated.
4.3 RFP Proposed Project Schedule
March20"2017
Aoril3.2017
April7,2017
Aoril21.2017
Mav 10.2017
Avista issues RFP
Bi dder's Questions/Requests for Clarifi cation Due
Avista's Responses to Clarifications Due Date
Proposals Due
Successful Bidder selection and announcement
Contract and Statement of Work ExecutedMav 17.2017
5.0 RFP PROCESS
5.1 Pre-proposal Questions Relating to this RFP
Questions about the RFP documents (including without limitation, specifications, contract terms or
the RFP process) must be submitted to the SPC (see Section 4.1), in writing (e-mailed, faxed, or
addressed in accordance with Section 4.2, by the Due Date. Notification of any substantive
clarifications provided in response to questions will be provided via email to all Bidders.
5.2 Requests for Exceptions
Bidder must comply with all of the requirements set forth in the documents provided by Avista as
part of this RFP (including all submittals, contract documents, exhibits or attachments). Any
exceptions to these requirements must be: (i) stated separately, (ii) clearly identify the exceptions
(including the document name and section), and (iii) include any proposed alternate language, etc.
Failure by Bidder to provide any exceptions in its Proposal will constitute full acceptance of all
documents provided by Avista as part of this RFP. While Avista will not consider alternate language,
etc. that materially conflicts with the intent of this RFP, Avista may consider and negotiate the
inclusion of terms that would be supplemental to the specific document if such terms reasonably
relate to the scope of this RFP.
5.3 Modification and/or Withdrawal of Proposal
5.3.1 By Bidder: Bidder may withdraw its Proposal at any time. Bidder may modify a submitted
Proposal by written request provided that such request is received by Avista prior to the Due
Date. Following withdrawal or modification of its Proposal, Bidder may submit a new
Proposal provided that such new Proposal is received by Avista prior to the Due Date and
includes a statement that Bidder's new Proposal amends and supersedes the prior Proposal.
5.3.2 By Avista: Avista may modify any of the RFP documents at any time prior to the Due Date.
Such modifications will be issued simultaneously to all participating Bidders.
5.4 hoposal Processing
5.4.1 Confidentiality: It is Avista's policy to maintain the confidentiality of all Proposals
received in response to an RFP and the basis for the selection of a Bidder to negotiate a
definitive agreement.
5.4.2 Basis of Any Award: This RFP is not an offer to enter into an agreement with any party.
The contract, if awarded, will be awarded on the basis of Proposals received after
consideration of Bidder's ability to provide the services/work, quality of personnel, extent
and quality of relevant experience, price and/or any other factors deemed pertinent by
Avista, including Bidder's ability to meet any schedules specified in the Statement of Work.
5.4.3 Pre-award Expenses: All expenses incurred by Bidder to prepare its Proposal and
participate in any required pre-bid and/or pre-award meetings, visits and/or interviews will
be Bidder's responsibility.
RFP No. R-40239 Page 4 of9
Avista Corporation
East 14l I Mission Ave.
Spokane, WA99202
4,i-trsrA
5.4.4 Proposal Acceptance Term: Bidder acknowledges that its Proposal will remain valid for
a period of 60 days following the Due Date unless otherwise extended by Avista.
5.5 Contract Execution
The successful Bidder shall enter into a contract that is substantially the same as the Sponsored
Research and Development Project Agreement governing the performance of the Services/Work
applicable under this RFP included as Appendix B. However. those Universities that have prior
written asreements with Avista. may mutually agree to utilize those apreements with an extension
and some modifications to the documents.
6.0 PROPOSAL REQUIREMENTS AND SUBMITTALS
Bidder's Proposal must conform to the following outline and address all of the specified content to facilitate
Avista's evaluation of Bidder's qualifications; approach to performing the requested Services/Work; and other
requirements in the SOW. Proposals will be evaluated on overall quality of content and responsiveness to the
purpose and specifications of this RFP, including the information set forth in Section 6.5 below.
6.1 Proposal Process
Each eligible institution will be limited to TEN specific proposal submittals. One representative of the
eligible institutions will be responsible for submitting all of the proposals.
The proposal must not exceed 6 pages not including the appendices. The proposal shall be in 1 1 point
font, 1.5 spaced and one inch margins. The original and one electronic copy of the proposal (PDF -
Form) must be provided to Avista's point of contact listed herein.
6.2 Proposal Submittals The following items are required with Bidder's Proposal. Each proposal
shall contain the following project elements.
1. Name of Idaho public institution;
2. Name of principal investigator directing the project;
3. Project objective and total amount requested (A general narrative summarizing the approach
to be utilized to provide the required services);
4. Resource commitments, (number of individuals and possible hours for services);
5. Specific project plan (An outline of work procedures, technical comments, clarifications
and any additional information deemed necessary to perform the services);
6. Potential market path;
7. Criteria for measuring success;
8. Budget Price Sheet / Rate Schedule;
9. Proposal Exceptions to this RFP (if any);
10. Appendix A - Proposal Cover Sheet (last 2 pages of this document)
I l. Appendix C: Facilities and Equipment
12. Appendix D: Biographical Sketches and Experience of the principle investigators and / or
primary research personnel for each project (ifdifferent individuals for each project
submitted)
RFP No. R-40239 Page 5 of9
Avista Corporation
East l4l I Mission Ave
Spokane, WA99202 ^#vtsrA
6.3 Proposal Cover Sheet
Bidder must fill out, sign and date the attached Proposal Cover Sheet. The signatory must be a
person authorized to legally bind Bidder's company to a contractual relationship (e.g. an officer of
the company).
6.4 Institution Information
o Institution Oualifications
Bidder shall provide information on projects of similar size and scope that Bidder has
undertaken and completed within the last five years. Please include a list of references on
Appendix A that could be contacted to discuss Bidders involvement in these projects.
Institution Resources
Identify any unique or special equipment, intellect, hardware, and software or personnel
resources relevant to the proposed Services that Bidder's firm possesses(list in Appendix D).
o Project Personnel Oualfrcations
Provide a proposed organization chart or staffing list for a project ofthis size and scope and
identify the personnel who will fill these positions. If applicable, identi$ project managers who
will be overseeing the Services and submit their resume identifying their work history, (please
see Section 6.2, question #4).
o Approach to Subcontractins
If Bidder's approach to performing the Services will require the use of subcontractors, include
for each subcontractor: (a) a description oftheir areas ofresponsibility, (b) identification ofthe
assigned subcontractor personnel, (c) resumes of key subcontractor personnel, (d) a summary
of the experience and qualifications of the proposed subcontracting firms in work similar to
that proposed, and (e) a list ofreferences for such work.
6.5 Evaluation Criteria
Avista will evaluate each proposal based upon the following criteria:6.5.1 Project Requirements. Strength ofProposal
. Responsiveness to the RFP
o Creativity in Leveraging Resources
. Samples of Work Products
o Overall Proposal (Complete, Clear, Professional)
6.5.2 Strength & Cohesiveness of the Project Team
Overall ability to manage the project
Technical ability to execute the Services
Research/analysis ability
Project milestones with clear stage and gates (annually)
Overall team cohesiveness
6.s.3 Qualifications and Experience
Experience working with electric utilities
Project management and multi-disciplined approaches
Experience working with organizations in a team atmosphere
a
a
a
a
a
a
O
a
RFP No. R-40239 Page 6 of9
Avista Corporation
East l4l I Mission Ave.
Spokane, WA99202
AHvtsrA
7,0 RESERVATION OF AVISTA RIGHTS:
Avista may, in its sole discretion, exercise one or more of the following rights and options with respect
to this RFP:
. Modify, extend, or cancel this RFP at any time to obtain additional proposals or for any other reason
Avista determines to be in its best interest;
. Issue a new RFP with terms and conditions that are the same, similar or substantially different as
those set forth in this or a previous RFP in order to obtain additional proposals or for any other reason
Avista determines to be in its best interest;
o Waive any defect or deficiency in any proposal, if in Avista's sole judgment, the defect or deficiency
is not material in response to this RFP;
o Evaluate and reject proposals at any time, for any reason including without limitation, whether or not
Bidder's proposal contains Requested Exceptions to Contract Terms;
. Negotiate with one or more Bidders regarding price, or any other term of Bidders' proposals, and
such other contractual terms as Avista may require, at any time prior to execution of a final contract,
whether or not a notice of intent to contract has been issued to any Bidder and without reissuing this
RFP;
. Discontinue negotiations with any Bidder at any time prior to execution of a final contract, whether
or not a notice ofintent to contract has been issued to Bidder, and to enter into negotiations with any
other Bidder, if Avista, in its sole discretion, determines it is in Avista's best interest to do so;
. Rescind, at any time prior to the execution of a final contract, any notice of intent to contract issued
to Bidder.
[END OF REQUEST FOR PROPOSAL INSTRUCTIONS AND REQUIREMENTS]
RFP No. R-40239 PageT of9
Avista Corporation
East 14l I Mission Ave.
Spokane, WA99202 ^#vtsr
APPENDIX A - Proposal Cover Sheet
Bidder Information
Organization Name:
Organization Form:
(sole proprietorship, partnership, Limited Liability Company, Corporation, etc.)
Primary Contact Person Title
Cit., Stata 7i^-
Telephone:_ Fax:_ Federal Tax ID#_
Name and title of the person(s) authorized to represent Bidder in any negotiations and sign any contract that may
result ("Authorized Representative") :
If classified as a contractor, provide contractor registration/license number applicable to the state in which
Services are to be performed.
Provide at least three references with telephone numbers (please verify numbers) that Avista may contact to
veri$ the quality of Bidder's previous work in the proposed area of Work.
REFERENCENo. I
Organization Name:
Contact Person:
Project Title:
Telephone:
Fax
Email
REFERENCE No. 2
Organization Name:
Contact Person:
Project Title:
Telephone:
Fax:
Email
REFERENCE No. 3
Organization Name:Telephone:
Fax:
RFP No. R-40239 Page 8 of9
E-mail Address:
Avista Corporation
East l4l I Mission Ave.^#vtsrfrwA99202
Contact Person:
Project Title
Email:
By signing this page and submitting a Proposal, the Authorized Representative certifies that the following
statements are true:
1. They are authorized to bind Bidder's organization.
2. No attempt has been made or will be made by Bidder to induce any other person or organization to submit
or not submit a Proposal.
3. Bidder does not discriminate in its employment practices with regard to race, creed, age, religious
affiliation, sex, disability, sexual orientation or national origin.
4. Bidder has not discriminated and will not discriminate against any minority, women or emerging small
business enterprise in obtaining any subcontracts, ifrequired.
5. Bidder will enter into a contract with Avista and understands that the final Agreement and General
Conditions applicable to the Scope of Work under this RFP will be sent for signature under separate cover.
6. The statements contained in this Proposal are true and complete to the best of the Authorized
Representative's knowledge.
7. If awarded a contract under this RFP, Bidder:
(i) Accepts the obligation to comply with all applicable state and federal requirements, policies,
standards and regulations including appropriate invoicing of state and local sales/use taxes (if any) as
separate line items;
(ii) Acknowledges its responsibility for transmittal of such sales tax payments to the taxing authority;
(iii) Agrees to provide at least the minimum liability insurance coverage specified in Avista's attached
sample Agreement, if awarded a contract under this RFP.
8. If there are any exceptions to Avista's RFP requirements or the conditions set forth in any of the RFP
documents, such exceptions have been described in detail in Bidder's Proposal.
9. Bidder has read the "Confidentiality Notice" set forth on the second page of these "INSTRUCTIONS
AND REQUIREMENTS" and agrees to be bound by the terms of same.
Signature:Date:
'T'T,I. THIS PAGE MUST BE THE TOP PAGE OF BIDDER'S PROPOSAL ***
RFP No. R-40239 Page 9 of9
APPENDIX C
University of ldaho Agreements
fr:ststa X
PROJECT TASK ORDER for SERVICES
Master No.Task Order No.Modification No.Modification Date
MA, Ul/Avisfa R-39872 02 for 2017
This Task Order is made and entered into this 28 day of June, by and between Avista
Corporation, herein called SPONSOR, and the University of ldaho, herein called
UNIVERSITY. The Task Order describes aclivates to be conducted by UNIVERSITY for
SPONSOR. Any deviation from the work outlined in this Task Order and Attachment A
must first be approved in writing by SPONSOR. ln addition, work performed under this
Task Order is subject to the provisions of the Master Services Agreement. The Master
Agreement, and this Task Order and Attachment A constitute the entire agreement for
the WorU Services applicable under this Task Order. The terms and conditions of this
Task Order may not be modified or amended without the express written agreement of
both parties.
Title of Services:
Robusl Microgrid for Dox'ntot n Spokone
Start Date:
08-01-2017
Duration (number of months)
12
Estimated completion date:
08-31-2018
UI PI:
Herbert Hess
SPONSOR Representative:
Heather Rosentrater
Consideration and Payment:
Ul agrees lo perform the Services set forth in Aftachment A, Scope of Services, and SPONSOR
agrees to pay for said Services listed as budgeted amounts upon performance by Ul. The
obligation and rights of the parties to this Task Order shall be subject to and governed by terms
and conditions of this Task Order and the Master Agreement.
Funding Amount ($): (Per Attachment A, Budget)
$83,712.89
Deliverables:TN
Progress Report Date:
Final Report Date!!j3,!j!0,lllfl ottrer:
lN WITNESS WHEREOF, the parties hereto have set their hands on the day and year
first written above:
Ul Representative Signature Age n cy Representative Si gnature
Deborah N.
-!E:i*&r.Snaver
Deborah Shaver, Director
Date:
Heather Rosentrater VP
Date: -7 lL1 l11
4 ?.:.e.r?
Framcwork for Siting and Sizing Energy Storage for Enhanced Performance of thc Avisa System
Univcrsity of Idaho
Principal Investigator:Hcrbert L. Hcss
Co-Principal Investigator: Brian Johnson_
Co-Principal Investigator: Yacine Chakhchoukh_
Total Amount Requested: $83,7 I 2.t19
Objective
The obicctive of this work is to develop a possible framework for identifying locations for battcry
storage systems in the Avista transmission and distribution system based on the potential bencfils cncrgy
storagc locatcd at a spccific location in the Avista system. Thcrc are multiple benefits energy slorage can
provide, including balancing sen ices for variable generation, reducing up and down ramping on
responsive gcncration to reducing heating and wear on the gcncration, local load support, and cnabling
portions of the system to become microgrids. Power and encrgy ratings for thc cnergy storage will be an
aspect of sizing and siting thc energy storage, as will response rate and potcntial rcactive power capacity.
This work extcnds and cxpands the results from thc aspects of current Dou,ntown Microgrid projcct
related to application ofenergy storage and potential synergies between photovoltaic generation and
cncrgy storage. Advantagc to the ratepayers will be measured through potential improvemcnts to system
operational margins and system operational efficiency.
Resource Commitment and Student Involvement
Rcsource commitments lbr this project include the following:
* PI and co-PI research time as normal academic duties.
* One graduate student in computer science as a funded Research Assistant to crcate and tsst the
software that underlies this energy trading systcm.
* One undcrgraduate student as a funded Rcsearch Assistant to create a model of the clectrical
system for software and hardware simulation.
* Real Timc Digital Simulator (RTDS). This is already fully complete and operating at thc
university. Existing university assets are appropriate and suflicient.
Details are contained in the Budget and Budget Juslification.
This project involves students in every part of the research: project definition, modeling of the systcm
and its componcnts, crcating the software, performing the simulation studies, analyzing thc results of
those simulations, creating proof-olconcepl prototypes, analyzing and tcsting thcsc prototypcs, and
making recommendations for means to further invcstigatc and implcment discoveries. We have employed
a team like this on a number of projects of similar scope and purpose in the past. Students are ma.ioring in
Computcr Science and in Electrical Engineering with an expectation to be involved in the clectrical porver
industry. Having a sponsor likc Avista as the recipient of deliverables enhances studcnt pcrformancc
greatly. We have realized a great deal of success from teams of this composition and its combination of
tcchnical compctcnce and multiple levels of scniority and cxperience.
Project Tasks
l. Identify potenlial applications for energy storage defined on current applications.
2. Determine power ratings, ramp rates and stored energy capabilities of thc storage elements for
each application.
3. Categorize the applications based on thc ancillary services they provide. This includes local
vcrsus systcm levcl bcncfits.
4. Rcduce the set of potential applications in consultation rvith Avisra engineers.
5. Devclop an approach for sizing energy storage for the highcst priority applications starting from
practices in the literaturc. Include possible applications of distributed storage elements acting in
coordinated fashion.
6" Senior design team: Implcment modcls and for battery energy storage systems appropriate lbr the
applications in si.mulation studies, with a focus on one or two technologies in consultation with
Avista. Thc WECC models will be a stat'ting point. Control models will bc developed appropriate
for application.
Projcct Plan
l5 August 2017
29 August 201 7
l9 September 2017
5 December 2017
5 December 2017
Spring semcstcr 2018
30 April 2017
30 April 2017
Summer 2018
3l August 2018
Bcgin Proiect
Sclecl senior design team
Start to assemble candidate application listing
Stage gate l: Review of potential applications
Senior Design Review #l: Modeling techniques and methods of
Analysis
Develop application sizing practiccs for energy storage for highcst
priority applications from Stage Gate I
Stage gate 2: Prelimrnary results of sizing
Demonstration of battery modeling
Completing simulation models and studies. Validation.
Final report due
Potential Markct Path
This proicct develops the underlying engineering analysis procedurc for choosing sites to apply
cnergy storage and lo dctermine po*'er and energy ratings for thc energy storage for differcnt tlpes of
potcntial storage applications in the Avista system. Results from this projcct rvill help dctemrine whcre to
procccd with cncrgy storage technologies. If the technology appears to bccome feasible, then a timc
horizon can detcrmined and recommendations for dcveloping it further will bc made. Rcduccd scale
hardware studies can follow, creating and analyzing performance or: the Analog Model Power System
using the RTDS with power hardrvare in the loop at the Universiry of Idaho. If that shows promise,
cngaging cnergy deveiopment resources, for example through US Dcpartrncnt of Energy or State
innovation and cntrepreneurial lunding would follow. The rcsults may also suggest commercially
availablc tcchnologics that can instcad be implcmented on thc systcm. In that casc, an implcmcntation
plan for moving foru,ard for implcmentation to bencfit the system ratepaycrs will bc suggeslcd.
Deliverables to Measure Project Success
L Written final report of the results of these studies in the lormat approvcd by Avist"a.
2. Intcrim rcports and telephone conferences as specified above. Midterrn report in two-page format
as specified above.
3. Softu,are models, including softu,are for running on PowerWorld and on the RTDS
4. Battery model with application, including software for running on PowcrWorld and on thc RTDS
Proposal Exceptions
Per section 5.2 of the RFP, the University has described cxccptions to RFP requirements and
conditions in thc lcttcr daled 4/15/16 and includcd with Appcndix A.
Budget
A
B
c
Expense
PI/Faculty Salaries
PI/Faculty Benefits
(hmp :i/wu'rv. uidaho.edrlosplfr ingebenefitstable)
Student/ Post Doc / Grad / Undergrad Salaries
Student /Post Doc /Grad / Undergrad Benefits
(270:academic year; 7 .4oh= summer)
Student /Post Doc lGrad lUndergrad
Tuition & Insurance
III Salaries
Year I
$2,03 i.00
$ l.940.86D
E
F
57A,429.78
$s26.03
$43.460.00
G
H
I
J
K
L
IH Benefits
(<20lrrs weeV9o/o)
EquipmenUComputers
Supplies - Background check
Travel
Evaluation Costs
N{odilied Total Direct Cost (A" B, C, D, F-K)
F&A / Overhead
(https ://uww.uidaho. edu/research/faculty/resources/f-and-a-rates)
Direct Cost + F&A
Total amount of Request (M + E)
$0.00
$300.00
$500.00
$0.00
$48,757.89
9,71\)\ ))
$73,283.11
S83,712.89
50.3070
M
Budgrt Justification
Pl/Faculty Salaries: 2Yo of salary to administer project and mentor srudents
PVFaculty Bcncfits: University faculty fringe benefit rate is 25.90oh. Studcnt fringe benefit rarc is 2.40%
in the academic ycar and7.70% summer.
Student Salaries: Onc graduate student paid at the rate of 521.00 per hour for 780 hours (nominal 20
hours per week) during the acadcmic year and 440 hours (nominal 40 bours pcr week) during the summcr
Onc undergraduate student paid at the rate of $12.00 per hour for 585 hours (nominal l5 hours per rvcek)
during the academic year and 440 hours (nominal 40 hours per week) during the summer. One part-rimc
undcrgraduate studcnt paid at the rate of $ I 2.00 pcr hour for 292 hours (nominal 7.5 hours per wce k)
during thc acadcmic year and 220 hours (nominal 20 hours per week) during the summer.
Student bsnefits: %. Studenr fringe benefit rate is 2.4Yo in the acade mic year and 7 .70% sLrmmcr.
Tuition and insurance: Acadernic year graduate studcnt in-state tuition per studcnt at the ratc ol
St1,468.(r6 and health insurance at the rate of $1961.12. Summer health insurance is included in ths
pa),rnent for spring semestcr.
Equipmen/computers: We will continue to use computers and soliware from the previous ycar's pro3ect.
Supplies: Background check ofeach student and professor as required by university policy. Any money
not spcnt on background chccks may be spent as student or faculty salaries and bcnefits.
Travcl: Two trips to Ayista in Spokane to present results and to consult with Avista engincers and
managemcnt-
F&A lOr.erhead: Assessed at the rate of 50.3% of project direct costs except ruition.
Appendix C: Facilitics and Equipmcnt
Laboratorv:
The power system model lab is a facility provided by the ECE department and is located close to PIs
office. The lab is a fully operational faciliry dedicated to power system simulation and experiments. The
lab maintains an Analog Model Power System (AMPS). AMPS is a small scale power system. This
analog power system contains six buses which can be connected in different topologies to get various
nerwork configurations depending on the application. AMPS contains four transrnission lines where the
effective length can be varied, trvo variable source impedances, an infinite bus, two synchronous
machines (one of which has a commercial exciter and an adjustabie speed drive to emulate a prime rnover
and govemor), loads, breakers, relays, logic processors, and measurement devices, among olher
equipment. System components are equipped with monitoring devices to monitor real-time operation of
the power system. These measurement devices and sensors gather data from various system components.
This information is transmitted via various communications channels of the Power System. The
measurement devices are provided by Schweitzer Engineering Laboratories (SEL).
These SEL 734s are equipped with Phasor Measurement Units (PMUs) and transmit synchronized data.
The data from SEL devices can be accessed and visualized using a Human Machine lnterface (HMI)
through SEL real time automation controllers (RTACs). The laboratory also has a data concentrator and a
synchrophasor vector processor.
The laboratory has a real time digital simulator with fwo racks, providing the ability to model somewhat
Iarger systems with more generators. The real time digital simulator runs an electromagnetic transients
simulation and performs data inpuloutput in real time relative to common power systems measurement
equipment such as PMUs and relays. The 400 series relays described above can be connected to the
RTDS. We can apply the methods dweloped in the proposed project to calculate the optimal dispatch
ratio of generators and simulate that scenario on the small scale power system available at UI's power
system laboratory to verify the accuracy of the methods developed.
Comouters and Software:
The PI and Co-PIs of the proposed project have a personal PC in their offices. All the project personnel
have access to the departmental computer lab. All computers have a mix of licensed software and
freeware available. Through the current projects with Avista, the PI's have access to the same version of
Powerworld as Avista uses. In addition, the Pl's have the full license for PowerTech Lab's DSATools
software that can perform large scale power system simulations. DSATools is compatible with commonly
Appendix C-Facilities and Equipment Page 1 of2
uscd soft\yare in power industry (including PSLF and PSSE). All the computers within UI nerwork will
have access to DSATools various packages. Therefore, all the project pcrsonnel, including students" will
be able to use the aforementioned software for power system simulations. DSATools packages include:
PSAT (power flow analysis), VSAT (voltage stability and contingency analysis), TSAT (transient
analysis), and SSAT (small signal analysis).
Project personnel also have access to newly purchased adaptive computational server "tsig STEM"
sponsored by NSF autard 1229766: Hewlett Packard DL 980, 160 Cores CPU, 4 TB RAM, and 16 TB
disk, Linux OS. The machine supports up to 40 separate concurrent experimenlslsimulations each with 2
proccssor cores and 50 GB of memory, parallel computation across any number of processor cores. It is
able to manage large-scale simulations across hundreds of virtual machines each running small portions
of a parallel algorithm.
Appendix C-Facilities and Equipment Page 2 of 2
Appendix D: Biographical Sketchcs
Brian K. Johnson, Ph.D., P.E.
Professor of Electrical Engineering
Schweitzer Engineering Laboratories Endowed Chair in Power Engineering
University of ldaho, GJL 201, Moscow, Idaho 83844-1023
[phone] ; [e-mail]
Profcssional Preparation
Universiry of Wisconsin-Madison, Madison, WI Electrical Engineering
University of Wisconsin-Madison, Madison, WI Electrical Engineering
University of Wisconsin-Madison, Madison, WI Electrical Engineering
BSEE, I987
MSEE, I989
PhD, 1992
Appointmcnts
2004-present: ProfessorElectricalEngineering,Universityofldaho
2406-2012: Chair, Department of Electrical and Computer Engineering
1997-2004: Associate Professor, Electrical Engineering, University of Idaho
1992-1991:. Assistant Professor, Electrical Engineering, University of Idaho
Professional Registration :
Registered Professional Engineer (ldaho #8368)
Recent Publications
l. Taylor, D.I., J.D. Law, B.K. Johnson, and N. Fischer. "Single-Phase Transformer lnrush Current
Reduction Using Prefluxing," IEEE Transactions on Power Delivery,Yol.27, No. l, January
2012, pp.245-252.
2. K. Eshghi, B.K. Johnson, C.G. Rieger, "Power System Protection and Resilient Metrics"
Proceedings of the 2015 Resilience lleeh Phlladelphia PA, August l8-20, 2015
3. R. Jain, B. Johnson, H. Hess, "Performance of Line Protection and Supervisory Elements for
Doubly Fed Wind Turbires" Proceedings of the 2015 IEEE Power and Energt Society General
Meeting, Denver, Colorado, July 27-31,2015
4. A. Guzmin, V. Skendzic, M. V. Mynam, S. Mam, B. K. Johnson, "Traveling Wave Fauh
Location Experience at Bonneville Power Administation," Proceedings of the Internotional
Conference on Power Systems Transients (IPST2015/, Dubrovnik, Croatia, July 15-18,2015.
5. B. K. Johnson, S. Jadid, "Synchrophasors for Validation of Distance Relay Senings: Real Timc
Digital Simulation and Field Results," Proceedings of the International Conference on Power
Systems Transtents QPST21l5), Dubrovnik, Croatia, July l5-18,2015.
6. H. Li, G. Parker, B.K. Johnson, J.D. Law, K. Morse, D.F. Elger,'Modeling and Simulation of a
Page I of4
Appendix D: Biographical Sketches
High-Head Pumped Hydro Syslem," 2014 IEEE Transmission qnd Distribution Conference and
Exposition, April 20 I 4.
7. Y. Xia, B.K. Johnson, H. Xia, N. Fischer, "Application of Modern Techniques for Detecting
Subsynchronous Oscillations in Power Systems." Proceedings of the 2013 IEEE Power and
Energt Society* General Meelirg Vancouver Canada, lttly 2l-25,2013
8. Y. Xia, B.K. Johnson, N. Fischer, H. Xia, 'A Comparison of Different Signal Selection Oplions
and Signal Processing Techniques for Subsynchronous Resonance Detection," Proceedings ofthe
International Conference on Power Systems Transients (LPST21l3), Vancouver, Canada Juiy l8-
20,?013.
9. M.P. Bahrman and B.K. Johnson, "The ABCs of HVDC Transmission Technologies," IEEE
Power and Energt. Vol. 5, No. 2, pp. 32-44,March-April 2007..
Related Research Projects.
L B.K. Johnson and J. Alves-Foss, "TWC: Small: Securing Smart Power Grids Under Data
Measurement Cyber Threats", Syracuse University (subcontract of NSF funding). August 16,
201 5-August 15, 2018, $210,696.
2. B.K. Johnson and H.L. Hess, "Smart Wires for Increasing Transmission and Distribution
Efficiency," Avista Corporation, August 23,2415 - August 22,2A16, $75,044
3. H.L. Hess and B.K. Johnson, "Critical Load Serving Capability by Optimizing Microgrid
Operation," Avista Corporation, Oct l-2015 - Sept 30,2016, $79,856.
4. B.K. Johnson, "Online Synchronous Machine Parameter ldentification," Schweitzcr Engineering
Laboratories, lnc. August l, 2014-July 31,2016, $155,037.
5. B.K. Johnson, and H.L. Hess, "Modeling and Design Options for an All Superconducting
Shipboard Electric Power Architecture," Oftice of Naval Research, October 2013-September,
2015, $56,894
6. Johnson, B.K, J.D. law and D.F. Elger, "Renewable Energy Balancing," Shell Energy North
America, June I 1, 2012-March 31, 2013, $75,000.
7. Johnson, B.K. and J.D. Law. "Subsynchronous Resonance Risk Assessment and
Countermeasures," Laboratory for Applied Scientific Research (subcontract from Schweitzer
Engineering Laboratories, Inc.), March 31, 2012-J anuary 3 l, 20 I 3, $35,88 1 .
8. Johnson, B.K. and Hess, H.L, "Modeling of Harmonic Injections and Their lmpacts," Idaho
Power Corporation, $48,674, June 1,2006-August 15,2047.
Page2 of 4
Appendix D: Biographical Skctches
HERBERT L. STSS
Pro{bssor
Universiry of ldaho
Department of Electrical and Computer Engineering
Moscow, Idalo 838214-1023
Education
Ph.D., Electrical and Computer Engineering, Univ. of Wisconsin-Madison, 22 August 1993
S.M., Electricai and Computer Engineering, Mass. Institute of Technology, l5 September 1982
8.S., Applied Science and Engineering, United States Military Acaderny, 8 June 1977
Experience
Proibssor, University of ldaho, 2006-Present
Associate Professor, University of ldaho 1999-2006
Assistant Professor, University of Idaho, 1 993- 1 999
Reserve Research Engineer, US Army RDECOM, 2001-2005
Electrical Engineer, US Army RDECOM, 2A0l -2042
Ressrve Professor, United Stxes Military Acaderny, 1989-2000
Assistant Professor, United States Military Academy, I983-1988
Research Interests
Power electronic converters, great and small: on-chip rchitectures for switching power electronic
convsrters and their conslituent transistors, motor drives, power supplies, battery chargers and monitors,
large switching power convefiers, power quality.
Professional Membership
IEEE (Societies: IES, lAS, PELS, PES, EDS)
ASEE (Divisions: ECE, ECCD, lnstrumentation)
The Honor Society of Phi Kappa Phi (University of Idaho Chapter Pa^st President)
Page 3 of4
Appendix D: Biographical Sketches
Publications and Patents
[ ] Wiegers, R.*, D. Blackketter, and H. Hess, "A Method for Balancing Ultracapacitor Voluge Arrays in an Electric Vehicle
Braking System," International Journal of Yehicle Design, acceged for publication.
[2] Samineni, S.r, B. Johnson, H. Hess, and J. Law, "Modeling and Analysis of a Flywheel Energy Storage System for
Voltage Sag Correclion, IEEI Tronsactions on Industry Applications, XLII, I, January/February 2006, pp. I -l l.
[3] Maninez, J., B. Johnson, and H. Hess, "Power Serniconductors," IEEE Trawactions on Power Delivery, XX.3, July
200s. pp. ?A86-2094.
[4] Alahmad, M.', M. Braleyr. J. Nance*, V. Sukumari, K, 8uckr, H. Hess, md H. Li, "Microprocessor Based Battery
Powcr Management System Enhances Charging, Monitoring, and Protection Fcatures," Battery Power Products and Technolog,,
VIII, 6, November 2004, pp. I 7-19.
[5J Muljadi, E, H.L. Hess, and K. Thomas+, "Zero Sequcnce Method for Energy Rccovcry from a Variablc- Speed Wind
Turbinc Qenentor," IEEE Transaclions on Energt Conversion, XVI, I , March 2001, pp. 99-103.
[6] Johnson, 8.K., and H.L. Hess. "Active Damping for Electromagnetic Transients in Superconducting Systems." .IrfE
Transactions on Applied Superconductivity, IX, 6, June I 999, pp. 3 I 8-32 I .
[7] Hess, H.L., D.M. Divan, and Y.H. Xue*. "Modulation Strategies for a New SCR-Ba.sed Induction Motor Drive System
with a Wide Speed Range." /EfE Transoctions on Industry Applkarions, X)O(, 6, November-December 1994. pp. I I 56- l 163.
[8] Umans, S.D., and H.L. Hess. "Modeling and Analysis of the Wanlass Threc Phase Motor Configuration." IEEE
Transoctioas on Power Apparatus and Systems, CII, 9. September 1983, pp.2912-2921,
[9] Padaca, V.F., and H. Hess. "Voltage Sags Plague a Food Processing Facilily." Power Quality Assurance. VII. l, January-
February 1997 , pp. l -5 (invited technical article for relereed industry magazine).
[0] Pctcrson, J.N., and HL Hess, "Feasibility, Design and Construction of a Small Hydroelectric Power Gcncrafion Station
as a Student Design Project," American Socicty for Engincering Education 1999 Annual Confcrcncc, , Jul 99, Scssion 2633. Bcst
Pagrcr Ovcrall Confcrcncc.
fi ll Menzc, E.*, K. Buck+, H. Hcss, D. Cox, H. Li, and M. Mojarradi, Patent Pending, "High Voltage to Low Voltage Levcl
Shiftcr," US Patcnt #7,061,298, I 3 June 2006.
[ 2] Hess, H.L., and D.M. Divan, "Thyristor Bascd DC Link Current Source Power Convcrsion System for Motor Driven
Operation," U.S. Patcnt 5,483,140,9 January 9 1996
Page 4 of 4
Yacine Chakhchoukh, Ph.D.
Ass istant Pro fessor of Electri cal En gi neering
University of ldaho, GJLZl3, Moscow,Idaho 83844-1023
(208) 885- I 550; [e-mail]
Professional Prep aratio n
National Polyechnic School of Algiers, Algeria
University of Paris-Sud XI, Paris, France
University of Paris-Sud XI, Paris, France
Electrical Engineering
Electrical Engineering
Electrical Engineering
BSEE,2OO4
MSEE,2OO5
PhD,20l0
Appointments
2016-present: Assistant Professor, Electrical Engineering, University of Idaho
2015-2016: Project Assistant Professor, Electrical Engineering, Tokyo Institute of Technology,
Japan
2013-2015: Postdoctoral Fellow, Electrical Engineering, Tokyo Institute of Technology, Japan
2011-2013: Postdoctoral Fellow, Electrical Engineering, Arizona State University, AZ, USA
2009-201l: Postdoctoral Fellow, Electrical Engineering, Technical UniversityDarmstadt, Germany
2006-2009: Research Engineer, French Transmission System Operator, RTE-France
Products
Five Products Related to this Proposal
l. Y. Chakhchoukh and H. Ishii, "Enhancing Robustness to Cyber-Anacks in Power Systems
Through Multiple Least Trimmed Squares State Estimations," IEEE Transactions on Power
Systems, Vol. 31, No. 6, pp.43954a05, Nov. 2016
2. Y. Chakhchoukh and H. lshii, "Coordinated Cyber-Attacks on the Measurement Function in
Hybrid State Estimation," IEEE Transactions on Power Systems, Vol. 30, No. 5, pp.2487-
2497,Sept.}Al5.
3. Y. Chakhchoukh and H. Ishii, "Cyber Attacks Scenarios on the Measurement Function of
Power State Estimation," Proceedings of the 2015 American Control Conference (ACC),
Chicago, IL, 2Als,pp. 3676-3681.
4. Y. Chakhchoukh, V. Vittal and G. Heydt, "PMU based State Estimation by Integrating
correlation",IEEE Transactions on Power Systems,Y o1.29, No. 2,pp.617-626, March 2014.
5. A. M. Zoubir, V. Koivunen, Y. Chakhchoukh and M. Muma, "Robust Estimation in Signal
Processing: A Tutorial-Style Treatment of Fundamental Concep*," IEEE Signal Processing
Magazine, Vol.29, No. 4, pp. 6l-80, July 2012.
Five Other Significant Products
1. Y. Chakhchoukh, S. Liu, M. Sugiyama and H. Ishii, "Statistical Outlier Detection for
Diagnosis of Cyber Attacks in Power State Estimation", Proceedings of the 2016 IEEE
Pou,er and Energt Society General Meeting, Boston, MA, July 17-21,2016.
2. V. Murugessen, Y. Chakhchoukh, V. Vittal, G. T. Heydt, N. Logic and S. Sturgill, "PMU
data Buffering for Power System State Estimatorc",IEEE Power and Energt Technologt
Systems Journal, Vol.2, No. 3, pp.94-102, Sep.2015.
I
3. J. Quintero, H. Zhang, Y. Chakhchoukh, V. Vittal and G. Heydt, "Next Generation
Transmission Expansion Planning Framework: Models, Tools, And Educational
Oppornrnities",IEEETransactionsonPou*erSystems,Yol.29,No.4,pp. I9il-l918,July
2014.
4. Q. Zhang, Y. Chakhchoukh, V. Vittal, G. Heydt, N. Logic and S. Sturgill, "lmpact of PMU
Measurement Buffer lrngth on State Estimation and its Optimization," IEEE Transactions
on Pawer Systems, Vol. 28, No. 2, pp. I657-1665,May 2013.
5. Y. Chakhchoukh, P. Panciatici and L. Mili, "Electric load forecasting based on statistical
robust methods", IEEE Transactions on Power Systems,Yol.26, No. 3, pp. 982-991, Aug.
2011.
Synergistic Activities
1. IEEE Power and Energy Society (PES) Member
Collaborators & Other Affiliations
Collaborators and Co-Editors (17 total)
Vijay Vittal (ASU), Gerald T. Heydt (AStr, Hideaki Ishii (TokyoTech, Japan), Song Liu (Institute
of Statistical Mathematics, Japan), Masashi Sugiyama (University of Tokyo, Japan), Patrick
Panciatici (RTE-France), Lamine Mili (VirginiaTech), Abdelhak Zoubir (TU Darmsatdt, Germany),
Michael Muma (TU Darmsatdt, Germany), Hui Zhang (California ISO), Qing Zhang (MISO), Veera
Murugessen (Alstom Grid), Jaime Quintero (Universidad Aut6noma de Occidente, Columbia), Brian
K. Johnson (UI), Daniel Conte de lron (LT), Larry Stauffer (UI), Michael }{aney (UI).
2
PROJECT TASK ORDER for SERVICES
Master Agreement No.Task Order No Modification No.Modification Date
MA, Ul/Avlsta R-39872 01 'for 2417
This Task Order is made and entered into this 28 day of June, by and between Avista
Corporation, herein called SPONSOR, and the Regents of the University of ldaho,
herein called UNIVERSITY. The Task Order describes activates to be conducted by
UNIVERSITY for SPONSOR. Any deviation from the work outlined in this Task Order
and Attachment A must first be approved in writing by SPONSOR. ln addition, work
performed under this Task Order is subject to the provisions of the Master Services
Agreement. The Master Agreement, and this Task Order and Attachment A constitute
the entire agreement for the Work/ Services applicable under this Task Order. The
terms and conditions of this Task Order may not be modified or amended without the
express written agreement of both parties.
Title of Services:
Managing fttr Efficienc1, Based on Operative Temperatures
Start Date:
a8-01-2017
Duration (number of months)
12
Estimated completion date:
08-31-2018
UI PI:
Elizabeth Cooper
SPONSOR Representative
Heather Rosentrater
Consideration and Payment:
Ul agrees to perform the Services set forth in Attachment A, Scope of Services, and SPONSOR
agrees to pay for said Services listed as budgeted amounts upon performance by Ul. The
obligation and rights of the parties to this Task Order shall be subject to and governed by terms
and conditions of this Task Order and the Master Agreement.
Funding Amount {$}: (Per Attachment A, Budget)
$24,011.00
!xu
Progress Report Date:
Final Report Datel[;}! -l!0'!.!l
Other:
Deliverables:
lN WITNESS WHEREOF, the parties hereto have set their hands on the day and year
first written above:
U I Representative Signature Agency Representative Signature
Deborah N.-:----5naver
Deborah Shaver, Director
Date:
Heather Rosentrater VP
Date: J -Zr'\1
rg7.lli.l7
W
Namc of ldaho public institution
University of Idaho
Namc of principal investigator dirccting the projcct
PI: Elizabcth Cooper
Project Title - Objective - Amount Rcquested
Ma n a gi n g.[o r Effi t' i en a, B a s ed on Op er a I ive T-em pera lu re s
Project objective and total amount requested
Amount Requested: 524.01 I
Objective
Controlling a building based on both surface and air tempcratures could reduce energy consumption
and promolc heal&icr buildings. Most buildings manage their hcating or cooling based solely on zonc air
temperature. Evcn whcn the thermostats arc kcpt within a narrow band of 4oF, occupant cornplaints pcrsist
(Arcns, et al., 20 l0). A largc factor of human comfort is bcing misscd in conventional thcrmostats: the
inclusion of the mean radiant tempcraturc. Many previous studies have established that the tempcratures of
the surfaces surrounding us have a far greater impact on our comfort than the air tempcrature (Olescn 2007).
Imagine a driver gctting into a car that's been in tle sun all day - the air conditioning may be running, but
thc driver is still sweating for the first part of thc drive until ali thc surfaccs cool off. A better comforl mctric
is thc opcrative temperature u'hich is a mix of air and surfacc tcmpcratures. lrVhile opcrative tcmpcrature is
u'idcly used for predicting human comfort, rarely is it directly used in building conirols. A control systcm
that incorporatcs the operative lemperature of a zone would allow for a wider range of supply air
tcmpsratures and bettcr meet $e needs of occupants. The wider range of air temperaturcs would rcduce
cncrgy consumption and heip to capitalize on operational featurcs such as natural ventilation, night-flush and
optimized sct-points. The outline of the work is to profilc typical sctpoins found in operation, test altcmativc
control mcthods, and estimate potential savings. This study, based on extensivc data collection paircd with
cncrgy modcling, would provide key insights on how to bcst balance thcrmal comfort and cnergy savings for
small commsrcial office buildings in the Pacific Northwcst.
Controlling for opcrative temperatures can bc donc with rclativcly simple and inexpensive
instnrmcnts: thcrmocouples. No occupant suneys would be required and no opinions would be taken
(opinions arc highly variable and unique). lnstead, the research would rely only on cstablished thcrnral
comfort criteria based on operative temperatwcs and humidity readings takcn at thc sitc (ASHRAE 55-2013).
The simple shifi in control from air temperature to operative tempcrature may have a dramatic impact on
energy consumption.
Expanding just the air cooling setpoint by 5'F can save up to 27o/o of the rcnl HVAC energy (Hoyt et
al. 2014). Horvever, expanded setpoints are only i'iable if occupant comfort is maintained. While cstablishing
high cooling setpoints can save a lot ofenergy, i[thc occupant is uncornfortable, they u'ill either adjust thc
thermostai on their own or place considcrable pressure on the building operator to do so thus nullifying any
polential sa\.ings" Occupant satisfaction (or the lack thcrof; is the driving forcc bchind thcrmoslat
adjustmcnts. Up to $330 in productivity per ycar can be losl for each employcc whosc office en'r'ironmcnt is
ourside the bounds of ASHRAE 55's comfort setpoints (Tom 200ti). Thercforc, any thcrmostat control
schemc, operative or othenvise, should focus on comfo( so that the selpoints are not irnmediatcly changcd
afler they arc implcmented. Most energy modeling misscs fiis crucial interaction and instead assumes
standard sctpoints and setbacks. That is why the first phase ofthis rcscarch is to identily typical setpoints at
real buildings instead of relying on ideal assumplions.
This research would provide critical data to dctcrminc horv effectivc an opcrative temperature
stratogy might impact both energy and occupant comfort. An opcrative thermostat control schcmc focuscd on
comfort has a far greater likelihood of remaining in place. This work is an opportunity to leverage data
analytics, energy modeling, and comfort standards to inform efficient control schemes that both savc cnergy
and endure.
Rcsource commitments, (numbcr of individuals and possible hours for serviccs):
Personnel Houni cstimatc Dcscription
Dr. Jinchao Yuan, P.E 40 Provide ovcrall management of the projcct
and technical cxpcrtisc
Elizabeth Cooper 30 Provide project guidance, support
publication plan and market path approach
L. Damon Woods - PhD ME studcnt 150 Provide technical support and cxccutc daily
tasks of this project
TBD MS ME studcnt 350 Exccutc daily tasks of this pro.icct
Specific project plan
This work will begin rvith the research of typical thermostat scttings for buildings in Avista tcnitory
The baseline will be established through a mix of literature rcviews and contact with controls cnginecrs,
consultants, and building operators. \\hilc therc are cstablishcd guidclines for thcrmostat sctpoints and
setbacks, the goal of this research phase is to uncovcr what thc actual scttings typically arc. Ncxt, IDL will
coordinatc *'ith Avista to select one or morc building sites for analysis as casc studics. At thc sitc, the team
rvill choose one or morc spaccs insidc the building to study in dctail. Ncxt, an array of data loggers will be
instailed in those spaces to record surface tcmperaturcs, air temperatures, and humidity lcvcls for scvcral
wecks. Air vclocity mcasuremcrts and thermal imaging of the spaces will be performed during sitc visits.
The rcscarch tcam u,ill also gathcr thcrmostat rcadings and energy consumption data from thc cncrgy
managcmcnt system (EMS). Depending on the EMS typc and its data logging capabilitics, IDL will eithcr
usc thc EMS trcndlogs directly or augmcnt thc EMS data collcction with a secondary progmm such as
RI:P No. R-4l3tt7 Page 2
SkySpark or BuildPulsc. Thc IDL tcam has been using SkySpark to remotely monitor control setpoints at
multiple building sites lor other research and it has provcd useful when EMS recordings arc unrcliable.
With data Iiorn both the building syslem and the logger deployment, the rcscarch tcam will be ablc
to calculate thermal comfort conditions without the nced lor occupant surveys. Thc tcam will devclop a
simple energy model for the sitc(s) selected in the established, DOE software program, EnergyPlus. IDL will
r,alidate the modcl and its comfort predictions based on the data collcctcd at the site. Once it has been
verificd, thc rcsearch team will use the encrgy models of the case study buildings to tcst alternative control
strategies. The control strategies will be developed eithcr directly in EnergyPlus or with a sccondary software
developed at Larvrsnce Berkeley National Lab known as the Building Controls Virtual Test Bed (BCVTB)
(Haves, et al., 2007). The control sffategy will be simple in naturc - similar 1o an air-based thcrmostat, but
with a rveighting lactor for the surface tcmperalures to better manage thermal comfort and energy savings.
The new stratcgy will bc run in annual EnergyPlus simulations. The EnergyPlus models will be
informcd by thc temperature and thermostat data gathcred at the sitc instead of idcal assumptions. The
simulation rcsults,,vill be used to estimate energy savings and comfort impacts of incorporating surface
tcmperatures into thermostat controis. The goal of thc rescarch is to identify the savings possiblc by shifting
controls from thcir currcnt baseline settings to a strategy that is more in line with the dcmands of occupant
comlort. Bascd on the rcscarch findings. the dcvelopment of the ahernativc controls could provc useful and
markchblc [o controls cnginecrs, consul[ants. and building opcrators.
The research leam rvill document the process and establish a pathway for the controls industry to
develop and commercialize thc service . The research will highlight the potential savings and the value it
could bring to consumers. The documentation will detail the methods and bc pursued for publication as par(
of the thesis work of a master's studenl at thc IDL. Thc projcct will be carricd out in thc following phases:
Task I Proiect Planning and Renorting * Conduct team meetings and ongoing project updatcs. reports and
deliverables as required by Avista staff, pro.iecl rnanagement contractor and the PUC. Ongoing throughout
thc project.
Task 2 Establish Current Baseline Setnoints - The team will conduct a short literature re"'iew on typical
operationai sctpoints of small commercial offrce spaces in practice and wili reach oul to controls enginccrs,
consultants, and building operators in Avista territory to establish typical thcrmostat sctpoints in operation; l -
2 months duration.
Task 3 Select a Site - IDL will work with Avista to select between one and rhree small commcrcial office
buildings as case studies - perhaps including one model developcd in our past work with Avista. The tcam
rvill identily spaces within thc casc study buildings for detailcd analysis; l-2 months duration.
Trsk 4 Collcct Onerational Data * The research tcam will deploy an array of data loggcrs to collect surfacc
and air remperatures along with humidity levels. The team will work with the building operators to collect
data on encrgy consumption and thermostat setpoints either through EMS recordings or by linking thc
building controls to a program like SkySpark that can catalog this information; 6-7 months duration.
RIP No. R-41387 Pagc 3
Task 5 Devclon Enersl' lModcl - IDL will dcvelop a basic cncrgy model lor fte spaccs selccted in
EncrgyPlus for analysis. This u'ill follow Task 3 and bc in parallel wirh Task 4; 34 rnonths duration.
Task 6 Tcst Altcrnativc Controls - Using the cnergy model, IDL will tcst thermostat sctpoinls bascd on the
opcrative lcmpcrature instead of the air lcmpcrafure. This work rnay begin at thc start of thc proicct for
dcfauit buildrng modcls and will be relincd aftsr thc complction of Task 5, 3-4 months duration
Task 7 Estimate Savinss - The team will sludy encrgy simulation results comparing thc typical settings
lound in Task I against thc ahemative controls devclopcd in Task 6; Less than I month duration.
Task 8 Develon Workllow for Practitioners - The final task rvill bc a study of thc proccss that u,ill add to
the current literaturc and promote this technology sen'ice to further commcrcializ-ation techniques. This
documentation will be part of a master's student's academic work and publication in a confcrcncc oriournal
rvill be sought: I month duration.
Potential market path
Building opcrations could bcnefit greatly from operative tcmpcraturc control. Operativc tempcrature
control would allow for rvider air tcrnperature serpoints, thus saving energy each ycar. Increasing thc cooling
setpoint by 5"F has bcen shown to reduce total HVAC energy by 27% (Hoyt et al. 2014). A study by thc
Pacific Norlhrvcst National Lab cstimated slightly more conservativc savings: a 2oF adjusrmcnt on both
heating and cooling setpoints led to a fairly uniform HVAC energy savings of 12-20% (Fernandcz ct al.
201 2). Nationwide, such savings would be equivalent to 370-61 5 trillion Btu savcd annually (EIA 20 I 2).
This research locus rvill be decidedl,u- narrower in scope: focusing purely on small commcrcial olllce
buildings in the Pacific Northwest, whcrc HVAC energ.v is typically 3-5% of thc annual load (ElA 2012), a
thermostat resct could result in savings of 1-7% of annual cncrgy consumption per building (Hoyt et al.
2014). A rcccnt bascline study of buildings in the Pacific Nonhwest found averagc officc building annual
encrgy usc to be ll2 kBtu/ft2 with an averagc office building size of 20,000 ft2. (Baylon, ct a1.,2008). Given
these assumptions, opcrative controls could save 25,000 - 45,000 kWhlyr for an average officc building.This
reprcsents only a general estimate, and it rvould take the rcscarch phases of Taskl and Task 5 to predict
firmer numbcrs. Horvever, it is possiblc the adoption of opcrativc thermostats by controls cnginecrs and
consultants could quickly scale up and result in widespread savings. In addition to cnergy savings, the
operative temperaturc control could dramatically enhance occupant comfort, thus making it an attractive
service to olfcr to clicnts.
The controls rely on several thcmrocouples which are inexpcnsivc and rvidely availablc sensors that
can be easily integrated into a control scquence. The report rvill providc a stcp-by-step methodology
including a demonstralion of how this control could be implemented at one of the sites being analyzcd so that
olhers may replicate and build on this. As the operative temperature control approach is adoptcd, the
technoiory allows cithcr building managcrs or utilify companies to provide inccntives for this typc of control
if savings arc vcrificd. A simple control scheme using operative temperatures will encouragc elficient control
RI-P No. R41387 Page 4
setpoinls that endure. The markct path may include the adoption of this control strategy by a controls
company or as a ne'w'tool used by consultants and building operators.
Critcria for measuring succcss
o Project team has coordinated u'ith several building managers and control personel to gathcr current
operational data and setpoints.
o Projcct tcam has logged surface and air temperaturcs to creale thennal comfort profilcs of sclecred
spaccs based on ASHRAE 55 criteria.
r Project team has crealed simple Energy"Plus models to rcflect the geometry and thcrmal properties of
the selected spaces.
o Project team has tesled operative tcmperature conrol schemes on the encrgy model and comparcd
thc cnergy consumption and comfort prcdictions t,o the original thermostat settings.
. Project team is able to estimate typical energy savings for small commercial office buildings in the
Pacific Northwest and present a replicable work flow with a control scheme thal could be
implemented into a case shrdy.
Budgct Pricc Shect / Ratc Schedule
Expcnsc
Pl.{Faculty Salaries (Cooper and Yuan)
P[Taculty Bcnefits (Coopcr and Yuan)
Graduate Student Salanes
Graduate Studcnt Wagcs
Student Benefits
Graduate Student Tuition Rcmission (partial)
Travel
F&A lOverhead (Excludes Tuition)
Total $ 24,011
Budget Justification
***All Hourly Rales are aversges ovtr FY|7 and Fa|8
Salaries -Support Requestcd from Elizabeth Cooper at 30 hours ($54.87/hr), Jinchao Yuan at 40 hours
($40.95/hr), and one graduate student at 350 hours ($ 1 5.00rhr), and one gradualc studenl at I 50 hours
($21.00/hr)
Fringe * Estimated based on the following rales'.25.9/o Faculty, 2.4% Students
Tuitbn Remission - Estimated tuition costs for one graduate student for Fall ot2017 and Spring of 2018
$3,365
$ 3,284
850
5,250
3,r50
202
3,365
I,000
6.9 t0
RI:P No. R-4l3lJ7 Page 5
Trsvel- Estimated fiavel expenses for project period S 1,000, to include: (l ) trip to Spokane for final
presentation to Avista for PI and graduate studcnts.
F&A/Ot'erhead -lDL is considered an on-campus unit of the University of Idaho u'ith a federally negotiated
rate of 50.3%.
Proposal exceptions
Per section 5.2 of the RFP, thc Universily has describcd exceptions to RFP requircments and condirions in
the lettcr datcd4ll2ll7 and included with Appendix A.
References
Arens E, Humphreys M, dc Dear RJ, Zhang H. (2010). "Are 'Class A' lemperalure requirements rettlislic or
desirable? " Building and Environmcnt 2010; 45 ( I ) :,1- 10.
ASHRAE. Standard 55-2013: "T'hermal environmenlal conditions lor human occupanc),. " Amcrican Society
of Heating, Rcfrigerating and Air-Conditioning Engineers (ASHRAE).
Baylon. David., Robison, Darid., Kennedy, Mike. (2008) . "Baseline Energ, LIse Index of the 2002-2004
NonresidentiaI Sector: Idaho, Montana, Oregon, ond lTashinglor." Ecotope
ELA Commercial Building Energy Consumption Sun'ey - El. Major fuel consumption by end use, 2012
Fernandez, N. ct al., (2012). "I)nergy Salings Modeling of Stondard ()ommercial Building Re-luning
Meanrres: Iarge Office Buildings " Pacific Northwest National Lab Report 21596.
Haves, Philip., Xu, Pcng.. (2007). "The Building Controls Yirtuql Tel Bed * A Sirulalion Environmenl for
Det,eloping ancl Tesling Control Algorilhms, Slrategies, and S),slems." Proc: Building Simulation 2007.
Olesen, 8.W., ct. al. QA07). "Operative Temperolure Conlrol cf Radiant Surface Heating and Cooling
S)'stems " Proceedings of Clima 2007 Wellbeing Indoors.
Hoyt" Tyler; Arcns, Edward; & Zhang, Hui. (20i4). "Extending air temperature setpoinls: Simulaled en€rg)
,salirgs ond design consideralions.for ne:w antl relretfit huildings. " Building and Environment 2014: 9 (10).
Tom, Steve. "Managing energf;i and comfort. " ASHRAE Journal 50.6 (2008); l8-27.
RIrP No. R-41387 Pagc 6
Appe ntlix C - Facilitics and f,quipment
University of Idaho - lntegraled Design Lab (UI-IDL) Facilitics and Equipmcnt
Overview
Thc UI-IDL occupics about 4,000 SF in dorvntown Boise. It includes a large classroom, thrcc confcrcnce
rooms and olfice and laboratory space. The IDL maintains a library of ovcr 900 devices for measurcmcnt
and data logging olcncrg.v cfhcicncy and human comfort parameters. Computational platforms includc
windows, Linux and Unix machines, including high performance u'orktations and a modest computing
cluster. Thc u'ebsite (rvwu,.uidaho.cdulidl) scrves as an outrcach conduit to the public, hosting archivcd
video lecturcs, rcscarch products, and an cquipmcnt listing. The UI-IDL maintains a wide range of
sofi.rvare Iiccnses and capabilitics rclatcd to energy efficacy and human factors rcsearch, data anal.vsis and
processing, and visualization, dcsign and graphics (see list below).
Institutional Qualifications & Recent projccts
Thc UI-IDL team has completcd over $6M in energy efficicncy rcscarch and cducation sincc 2004 and
has cxtensivc experience managing proiects ofthis scale and size. The figure bclow rcprcsents the
currcnl organizational chart of the UI-IDL.
University4ldaho
Brzabcth Copr&.:w Ark:.r q#s
&Tretr
LcyL Slnati
Dylan A3re Chiomyc Patil
d#*
D.lM YJmds Jinchao Yurn Ph.o\?r.t.\a* at glde Nrcl HMran
RIrP No. R-4l3ll7
S.an Roain N"h. Po(hr6t
Page 7
$m Osbore
gudger
6prfidllt.l
&
R nd, Tell
Architnclcrt
t h.rd
Selected projecls of similur size and scope from previous five years. References and work sumples
ovailable upon reqaest.
l. Title: Advancing Energt Efficiency
Confract u'ith: Northwest Energy Efficiency Alliance
Dates: 0ll20l5 - l2l20l7
Amount: $232,200
PI: Elizabeth Cooper
Co-Investigators: Damon Woods, Jinchao Yuan
2. I'itle: Aclvanced Energy Efficiency- 2015-2017 (comprises multipleprolects rungingfrom 530-
$150K annualll)
Contract with: Idaho Power Company
Dates: 0l/201 5 - l2l20l7
Amount: Approximately $1.1 M
PI: Eliz:beth Coopcr
Co-lnvestigators: Leyla Sanati, Jinchao Yuan
.f. Title: Governmenl Leading fui Example
Contract with: Idaho Officc of Energy Resources
Dates: 07/2016 - 0612017
Amount:$15,000
PI: Elizabeth Cooper
Co-lnvestigators: na
4. I'ille: At ista Advanced Enerp, Research * Using Reduced-Order Models for Simulation-Bosed
(- omm i ss i on i n g of Bu i I d i n gs
Contract with: Idaho Ar.ista Corporation
Dates: 08/2016 - 0912017
Amount: $64,000
PI: Elizabeth Cooper
Co-PI: Jinchao Yuan
5. Title: Goternmenl l.eading by Example
Contract with: Idaho Office of Energy Resources
Dates: 071201 5 - 06/2016
Amount:$26,000
PI: Elizabeth Cooper
Co-lnvcstigators: na
6. Title: Advonced Energ, Efficienq,- 2013-2015 (comprises l2 projects rangingfrom $30-$150K
annually)
Contract with; Idaho Power Company
Dates: 0l/2013 - l212015
Amount: $1,130,140
PI: Kevin G. Van Den Wymelenberg
7. T'ille: 2013 Kilov,att C.raclulown
Contract with: Northwest Energy Efficiency Alliance & JDM Associates
IlfP No. R*ll3lJ7 I)age ll
Dares: 0 I/201 3 - l2i20l3
Amount: $70,795
PI: Kerin G. Van Dcn Wymelenberg
Co-lnvesti gators: Brad Acker, Katie Leichliter
Co-Investigators: Ery Djunaedy, Gunnar Gladics, Jakc Dunn, Brad Acker, Julia Day
8. Title: Identificalion of Discom-fort Glare Sources from Verlical Fenestralion and Occupant
Control Scenqrios
Contract u,ith: Illuminating Engineering Sociery of No(h America
Dates: I 1 2012-ll/2013
Amount: $25.000
PI: Kevin G. Van Den Wymelenberg
Co-lnvestigators: Ery Djunaedy; Mark Changizi, O2Amp
9. T'itle: Oregon (\tde Energ,Savings Simulotion
Contract with: Oregon Departmcnt of Energy
Datcs: 06/20 12 - A9l2Al2
Amount: $35,000
PI: Kevin G. Van Den Wymelenberg (for UI-IDL)
Co-Investigators: Ery Djunaedy
10. Title: 2012-2013 Evaporative Roof-rop tinit Efficienqt M&V
Contract with: Northwest Energy Efficiency Alliance
Datcs: 0512012 - l2/2A13
Amouni: l$37,500
PI: Kevin G. Van Den Wymelanberg
Co-lnvesti gators: Brad Acker
R['P No. R41387 l)age 9
UI-IDL Software Capabilities
Simulation Programs:. OpcnStudio. EncrgyPlus. Radiance. Daysim. Autodesk Ecotcct. Therm. WUFI. AGI32. COI\,{FEN. gQUEST. Autodcsk Projcct Vasari. Simergy. TRNSYS
3d modeling programs. Autodesk Revit. Autodesk Autocad. Trintblc Skctchup. Rhinoccrous
Climate Analysis Programs. IDL Climatc Tools Sprcadshccts (http:li idlboisc.comldcsign+oollui-idl-climate-design--resources-lst-
2n d-qcn cration+oolscts). Clinmte Consultant
Encrgy Data Analysis. Encrgy Star Portfolio Manager
o E-Canr
o Unil'crsalTranslatoro E-Tracker. Energ-v Explorcrr SkySpark
Other Relatcdr R statistical studior MathWorks MATLAB
RIP No. R-41387 Page l0
Appendix D - Biographical Skctchcs
Elizabeth L. Coopcr
Dirccl.or, Univenity of ldaho - lntegratcd Design Lab
Associate Profcssor, Departmcnt of Architecture
306 S. 66 Strect
Boise, Idaho 83702
Work: (208) 101 -0644 Cell: (208) 7 6l -22A2
ecooper@)uidaho.edu
Education
o Universitv of lVashingtoa,2012
Master of Science, Environmental Healthr Univcrsifl' of Oregon, 2000
Master of Architectureo Nlount Holyoke College" 1994
Bachclor of Arts, Biological Scicnces
Professional Rcgistrations & Certifi cations
o Registcrcd Architect; Idaho (Lic.# AR-984441), Orcgon (Lic.# 5272)r Registercd Architcct;National Council of ArchitecturalRcview Boards (NCARB)o Accredited Professional (AP); U.S.G.B.C., L.E.E.D.
Professional Experience
o University of ldaho, Integratcd Design Lab, Boise,Idaho
Director, Associate Professor, Oct. 2015- Currento University of ldaho, Integrated Design Lab, Boise. Idaho
Rcscarch Assistant Profcssor, Interim Director, April 20 I 5- Oct. 20I 5o University of ldaho, Boise, Idaho
lrcturer, Department of Architecturc, 2005-20 I5o University of Washington, Dept. of Environmental Health, Scattle, WA
Research Assistant, 20 I A-2A nr TAO, PLLC, Boise, Idaho
Partner, 2006-20 I 5o Building Health, LLC, Boise.ldaho
President, 2013-20 I 5e Tamura & Associates. Boise. Idaho
Architect, 2002-2006o Cole Associates Architects, Boisc, Idaho
Projcct manager/Intcrn Architect, 20AA-2002
Selected Profcssion al Projc,cts
o /llyer's ltlg3 Apartmeirl.r. Eagle,Idaho. Completed 2015.
o Clcnd 9 Brev'e4t T'enunt lmprovemenl. Boise, Idaho. Completed 2014.o Banner Bank Baker ()6,'. Baker City, Oregon. Completed 2013.o Hope Plaza Apartmerls. Caldwell, Idaho. Completed 201 l.c I'he Matador Restauranl Tenant ImprovemenL Boise, Idaho. Completed 2009.
RFP tr*o. R-4 I 3 87 Page I I
. Ranner Bank Dou,ntov'n Boise Tenanl lmprot,emenL Boisc, Idaho. Completed 2007. LEED-CI
Gold. Citcd in, Williams, Homcr L. Building T1,pe Basics Jbr Banks and l"inanc'ial Insriu.rtions.
Hoboken, NJ:John Wilcy & Sons,20l0. Print.
c lhinding Creek Condominiums. Eagle, Idaho. Completed 2007.
o lirnut Residence. Boise, Idalro. Complcted 2004. Cited in Thrivc Magctzine, Dcccmbcr 2004.
Conferences rnd Presentations
o Idaho Energy and Grccn Buiiding Confercnce, Boise, Idaho. lntegraled De.sign Principles.
October 4-5,2016.
. Unitcd States Green Building Council, Montana Chapter, Big Sky, Montana. lnstitutionalizing
Healthy Buildings. January 22,2016
r Society for Risk Analysis Annual Mecting, San Francisco, California. Assessmenl of lhe
(lontribuliott of Indoor Surface Residues to SYOC txpo:;ure: Nicotine as e M<tclel Compound"
Deccmber 9-12,2012.
r United Stales Green Building Council, Idaho Chapter, Boise, ldaho. Healthl' Buildings: A neu'
para digm. September 6, 20 12.
o International Socicty of Exposure Scicncc Annual Mceting, Baltimore, Maryland. Assassmenl of
the Contribulion o/ Indctor Surfuce Residues to Children's Ni<'otine Exposure (poster). October
23-2'1,201t.
Synergistic Activitics
. Member, American Institute of Architectso Member, Amsrican Society of Heating, Refrigerating, Air-Conditioning Engineers
. Mcmber, lnternational Society of Exposure Sciencer Mcmber, Society of Building Science Educators
o Advisor, Advisory Board City of Boise Ordinance Review Committeer Advisor, Ada County Highway District Grecn Stormwater lnfrastructure Dcsign Guide Advisory
Group
RI:P No. R-41387 Page 12
Jinchao Yuan, Ph.D., P.E.
Rcscarch Associate Profcssor
College of Art and Architecture. Univcrsity of Idaho
Addrcss: 306 S 6th Street, Boise, ID 83702
Tel: 208-40 I -0649 (W); 6 I 7480-0366 (C)
E-mai I : j cyuan(a)u idaho.edu
f,ducation
Nlassachusetts Institute of Technologp, Cambridge, MA USA
Ph.D. in Building Technology, Septembcr 2007
Pennsylvania State Universi6, University Park, PA USA
N{.Sc. in Mcchanical Option of Architectural Enginccring, August 2003
Tsinghua University, Beijing, China
B.S. in Mechanical (Thermal) Engineering/Buitding Scicncc, July 200 I
Professional Expericnce
o Intcgraacd Design Lab, Collegc of fuchitecturc and Art, Univcrsity of ldaho
Rcscarch Associate Professor Jan 201 6 to Date
Conduct and lcad rsscarch work on topics related to high performance building and energy
elficicncy;
Develop and contribute to proposals for cxternal research funding opportunities as PI or Co-PIs.
o Olidcn Technology LLC, Sugar Land, TX
Senior Scisntist II / Consultant Dec 2013 to Jul20l5
R&D on directional Electromagnctic resistivity downhole tools on inversion algorithms,
firmwarc, software, mechanical system design, and electronic systcm designlanalysis.
r Nexant Inc.. Demand Management Division, Houston. TX
Scnior Proicct Engineer May 2009 to Aug 2013
Devcloped and implcmented encrgy cfficiency programs for utilitics clicnts national wide,
developcd models to estimate mcchanical system performance; contributcd to proposal
development, project bids, and budget planning: per{brmed program developmcnt sludics and
rcsearch.
o Transsolar Climate Engineering, Ncw York, NY
Project Engineer Dcc 2007 to Apr 2009
Consultcd on national-wide and internalional MEP hrms, architccts, and municipal authorities in
North Amcrica, Europe, Middle East, and Asia on sustainable building systcm dcsigns in lighting,
indoor airflow/thcrmal transpo( wind/solar power, and facade systems.
. Massachusetts Institute of Technology, Cambridge, MA
Rcscarch and Teaching Assistant Sep 2003 to Nov 2007
Developed ncrv methods based on dynamical systcm models to investigate thc solution
multiplicity and applications of statc transition methods in systcm stability identification and
hy'brid ventilation controls; Regular recitations, Q/As, and guest lecturing on fivc undergrad and
grad courses.
o Penns-_vlvania State University, University Park, PA
Rcscarch and Tcaching Assistant Aug 2001 to Aug 2003
Developed computational algorithms to couple multi-physics phcnomena in buildings (CFD, flow
nctwork, and heat transfer); numcrically and cxperimentally validate the developed codc.
Teaching Assistant for: CFD in Building Applications, F02; Fund. of HVAC, F0l & S02.
a
RFP No- R-41 387 Ilage l3
Grants/Awards
Co-PI. "lndustrial Assessmenl Center lor the Intennountain Wcst," DOE (subcontracting via Boise State
Univcrsity), Oct 20 I 6-Oct 2021'.
Co-PI. "Using Rcduced-Order-Modcls for Simulation-Based Commissioning of Buildings," AVISTA, Aug
2016-Aug 2017;
Best Studcnt Postcr Award. National Conference of IBPSA-USA. SimBuild 2006.
Sclected Publications
Yuan, J. and Glicksman, L.R., 201L "Nonlincar Bchaviors in Building Ventilation Systems (abstract),"
SIAM (Socicty of Industrial and Applied Mathcmatics) Confcrencc held in Snowbird, UT, May 201 I.
Yuan, J. and Glicksrnan, L.R., 201 l. "Dynarnical Aspccts and Design Implications lor Buoyancy
Chimney and Wind Scoop Vcntilation in a Natural Ventilated Building (cxtended abstracl)," Indoor Air
Confcrencc hcld in Austin, TX, June 2011.
Yuan, J. and Glicksman, L.R., 2010. "Using Statistical Mcthods to Investigate thc Mapping lrom Initial
Values to the Multiplc Stcady States in Complex Building Simulation Problems." SimBuild 2010, pp.
127433.
Yuan, J. and Glicksman, L.R., 2008. "Multiplc steady stalcs in combincd buoyancy and wind drivcn
natural vcntilation: the conditions for multiple solutions and thc critical point for initial conditions,"
Building and Environmcnl, vol. 43(l). pp. 62-69.
Srcbric, J., Yuan, J., and Novoselac, A., 2008. "On-site experimental validation of a coupled muhi-zonc
and CFD modcl for building contaminant transport simulations," ASHRAE Transactions, vol. I la(l), pp.
273-28t.
Yuan, J. and Glicksman, L.R., 2007. "Transitions bctween the multiple steady statcs in a natural
vcntilation systcm rvith combined buoyancy and wind drivcn flou,s," Building and Environmcnt, vol.
42(10), pp.3500-3516.
Yuan, J. and Glicksman. L.R., 2006. "Validation of a multi-zonc model rvith integrated encrgy Equation
and impact of thermal mass modcling methodology," SimBuild 2006.
Yuan, J.C. and Clicksman, L.R., 2005. "Multiple steady statcs in a combined buoyancy and wind drivcn
natural vcntilation System: necessary conditions and initial Ialues", IndoorAir 2005, pp. 1207-1214.
Yuan, J. and Srcbric, J., 2004. "Transient prediction of contaminant distribution by introducing energy
load calculations into multi-zone modeling," CiB World Building Congrcss 2004, I I pages, May 2-7,
2004. Toronto. Canada.
Yuan, J. and Srebric, L,20A2. "Improved Prsdiction of Indoor Conlaminant Distribution for the Enrire
buildings," ASME (Amcrican Society of Mechanical Engineers) Winter Mccting 2002, vol. 258, pp. I 1 l-
IIn.
Revicw Services
HVAC&R Rcscarch (Science and Technology for the Built Environmcnt). Building and Environment,
Building Simulation Conferences, Natural Science Foundation (NSF).
RF'I'No. R-4l3tt7 Iragc I,1
L. Damon Woods, E.I.T.
Rcsearch Assistant, University of Idaho * Integrated Design Lab
Ph.D. Candidale, Department of Mechanical Enginecring
30(> S. 6e Strcct
Boise, Idaho 83702
Work: [phone] Ce ll: [phone]
dwoods(Duidaho.cdu
Education
. Universiq of ltlaho, [Exp. 20171
Ph.D., Mechanical Engineering. Boise State University, 2013
Mastcr of Scicnce, Mcchanical Enginccringo Montana State University, 2010
Bachelor of Science, Mechanical Enginecring
Professional Experience
. Univcrsity of ldaho,lntegrated Dcsign Lab, Boise,ldaho
Research Support, 20 I 3- Current. Boisc State University, Boise, Idaho
Adjunct lnstructor, Applied Thermodynamics, Aug. 2014 - Dec.20l4. Alstom Power, Baden, Switzerland
Research and Development Intern, Aug 2013- Feb 2014o Boisc State Univcrsity, Dept. of Mechanical Enginccring, Boise, ID
Rcsearch Assistant, 201 0-20 12
Publications
Woods. D.. Noble, T., Acker,8., Budwig, R., Van Den Wymelenberg. K., Optimizing
Economizer Operation by Virtual Commissioning through Rcmotc Co-Simulation. Building
Simulation, San Francisco, CA, August 2017.
Woods. D., Mahic, A., Van Den Wymelenberg, K. Jennings, J., Cole, J., Simulation on Demand
Ibr Dccp Energy Retrofits, American Council for an Energy Efficient Economy Summer Study in
Buildings Confercncc, Asilomar, CA, August 2016.
Woods, Lindsay D.,2013, Simulation of Vawt and Hydrokinctic Turbines with Variable Pitch
Foils, Thcsis (M.S.) Boisc State University, 2013.
Damon Woods L., Gardner J.F.. and Myers K.S., Simulation of Vertical Axis Wind Turbines rvith
Variable Pitch Foils, ASME International Mechanical Engineering Congrcss and Exposition,
Procccdings (IMECE). 6 B. 2013.
Prcsentations
o Idaho Energy Conference, Boise, [D" Cold Feet - Managing Controls and Condensation lor
Radiant Slabs I llLl20l6
o ASHRAE Idaho Chapter October mecting Boise, ID Radiant Systcms and Controls l0l1212016
. f,nergy Policy Institute Research Conference, San Francisco CA: Using thc Time Dclay of
Radiant Syslcms to fie Grid's Advantage 09/05/2014
. Amcrican Wind Energy Association Annual Conference Poster Prcsentation, Anaheim, CA:
Simulation of Vertical Axis Wind Turbines using Simulink AyW20l3
a
a
a
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Itl:l) No. R-.113ti7 Page 15
PROJECT TASK ORDER for SERVICES
Master Agreement No.Task Order No.Modification No.Modification Date
MA, Ul/Avisfa R-39872 03 for 2017
This Task Order is made and entered into this 28 day of June, by and between Avista
Corporation, herein called SPONSOR, and the University of ldaho, herein called
UNIVERSITY. The Task Order describes activates to be conducted by UNIVERSITY for
SPONSOR. Any deviation from the work outlined in this Task Order and Attachment A
must first be approved in writing by SPONSOR. ln addition, work performed under this
Task Order is subject to the provisions of the Master Services Agreement. The Master
Agreement, and this Task Order and Attachment A conslitute the entire agreement for
the WorU Services applicable under this Task Order. The terms and conditions of this
Task Order may not be modified or amended without the express written agreement of
both parties.
Title of Services:
Aerogel Insulotion Syslem: An Innovative En*g; Efficient Thermul lYuil
Start Date:
08-01-2017
Duration {number of months)
12
Estimated completion date:
08-31-2018
UI PI:
Ahmed lbrahim
SPONSOR Representative :
Heather Rosentrater
Consideration and Payment:
Ul agrees to perform the Services set forth in Attachment A, Scope of Services, and SPONSOR
agrees to pay for said Services listed as budgeted amounts upon performance by Ul. The
obligation and rights of the parties to this Task Order shall be subject to and governed by terms
and conditions of this Task Order and the Master Agreement.
Funding Amount ($): (Per Attachment A, Budget)
$88,777.00
Deliverables:
Progress Report Date:
Final Report Date: 8€1'2018fl other:
lN WITNESS WHEREOF, the parties hereto have set their hands on the day and year
first written above:
Ul Representative Signature Agency Representative Siqnature
Deborah N. r:=!.=:E*,-.*_Shaver *:F*--*
Deborah Shaver, Director
Date:
Heather Rosentrater VP
Date: ? -z c-tl
rg 7.18.:?
Aerogel lnsulation System: An lnnovative Energy Efficient ThermalWall
University of ldaho
Pl: Ahmed lbrahim, Ph.D., P.E., Assistant Professor in Civil Engineering Department
CoPl: Behnaz Rezaie, Ph.D., P.Eng., Assistant Professor in Mechanical Engineering Department.
CoPl: Brian K. Johnson, Ph.D., P.E,, Professor and Schweitzer Engineering Laboratories Endowed Chair in
Power, Department of Electrical and Computer Engineering
Total funds reouested: S88,777
INTRODUCTION: Global energy and environmental issues call for urgent reduction of the energy
consumption and green gas emission in recent years. ln 2015, about 40% of total U.S. energy consumption
was consumed in residential and commercial buildings. As the economy growth and urbanization are
expected to continue, the energy consumption in the building sector will keep growing. ln the USA, energy
performance of buildings'administration promotes to renovate the existing buildings to meet the
minimum energy performance requirements. Most existing buildings in the US were built before building
energy efficiency was a concern, and most of these buildings will still be in function until 2025 or even
2050. lnstallation of thermal insulation is one of the most effective approaches to improve energy
efficiency of building envelopes, and lnsulation materials are the key tool in designing and constructing
energy efficient buildings. ln this proposal, the research team is proposing a new energy efficient thermal
wall insulation system using Aerogel.
OBJECTIVES: A new design of sandwich-like walls with aerogel blankets that will significantly enhance
thermal insulation of buildings is proposed. The system will consist of composite aerogel-blanket panels.
Thermal properties (thermal conductivity, thermal diffusivity and specific heat capacity) of the proposed
insulation system will be studied through comprehensive investigation through the literature,
manufacturers, in-situ applications and computer modeling. Field data will be collected in from an actual
building retrofitted with the Aerogel blankets. Modeling through (ADD) will be conducted for a building
as a case study. The case study will be modeled with the proposed sandwich panels and the traditional
insulation panels. Two full models will be simulated in Energy Plus lor monitoring the temperature
variation during summer and winters in Moscow ambient. The thermal effect of the aerogel sandwich
panels will be investigated by comparing the building heat loss with two different simulations. That heat
loss improvement will be interpreted into the energy cost saving for the building. Not only building heat
loss improvement is cost effective by using composite aerogel-blanket panels, but also the carbon foot
print of the building will be reduced. lt is anticipated that the heat transfer across building envelopes will
llPage
reduce the annual heat loss by 50% compared to the currently used insulation materials. ln addition, a life
cycle cost analysis with a full consideration of service life-cost will be performed and compared to the
currently used insulation materials
RESOURCE COMMITMENTS:
1. Research team time up to 10% commitment as normal academic duties plus 100 hours during
summer for all the principal investigators.
2. One graduate student as a funded research assistantto analyze data, and oversee undergraduates
3. One undergraduate student as a funded research assistant to work on a subset of the project and
collect data and help the graduate student during the project course.
Students will be involved in every aspect of this project. Teams like this have been employed at the
university for number of projects of similar scope and purpose in the past with great success. Students
are majoring in Civil, and Mechanical Engineering. A sponsor such as Avista, will significantly improve
stu dent performance greatly.
SPECIFIC PROJECT PIAN: Inergy sustainability is a crucial issue for the human's sustainable development
in modern era where is greatly dependent on high quality life and environment. Per the statistics, buildings
use about 4lo/oof lhe consuming energy everyyear, which results in a large amount of wastes and affects
the air quality, (11P,2012). Therefore, it is imperative to promoting the energy efficiency of buildings.
Currently, thermal insulation in modern buildings has become a crucial way to meet the demands of
energy efficienry codes, by reducing the conduction of heat through walls, ceilings, windows roofs and
floors effectively. Building insulations means using some materials as thermal insulation for reducing the
heat transfer in the construction or retrofit of building. Since maintaining a comfortable temperature in
buildings uses a large proportion of global energy, thermal insulation significantly help to reduce
unwanted heat loss and decrease the energy demand for heating and cooling systems. The effectiveness
of insulation is commonly evaluated by the key properties of a thermal insulation material*thermal
conductivity, thermal resistance, and thermal transmittance (or overall heat transfer coefficient). The
acceptable insulation materials need to achieve as low thermal conductivity as possible, which enables,
accordingly, a high thermal resistance as well as a low thermal transmittance.
Aerogel, also called solid smoke, is a synthetic porous material with remarkable properties. Aerogels are
dried gels with a very high porosity and were discovered in the early 1930s. Aerogel molecules do not
decompose at high temperatures and do not release harmful gases. Even at 800'C, its thermal
conductivity is only 43 mW(m . K). Precisely, they have high specific surface area (500- 1200 m2/g), high
porosity (80-99.8%), low density (3 Kg,/m3), high thermal insulation (1a mW(mK)), ultra-low dielectric
2lPage
constant (k=1.0-2.0) and low index of refraction (-1.05), A. Soleimani Dorcheh, (2008). Table 1 provides
an overview of the most important physical characteristics of silica aerogels. Due to these extraordinary
properties, in recent years, aerogels have attracted more attention and have been widely used in a variety
of technological areas such as aerospace, petrochemical, refining, municipal heating etc.
Table 1: Physical properties of silica aerogel, (Weina.Zhang,2006l,
The following sections show
the tasks to achieve the objectives Property Typical Values
Apparent Density 0.003-0.35 g/cm3
ofthe proposed idea.
Thermal Conductivity 13-16 mw/(m 'K), at 10 "C
20m@(m ' K) at static air
43 mwl(m ' K)at 800'C
Task 1: Literature Survev
The investigators will conduct
a com prehensive literature
survey for the up-to-date studies
related to implementation of
aerogel insulation in buildings.
The survey will report the state of
the art on the performance of walls
lnternal Surface Area 500-1000 m2fgram
Solid volume %o3.3-ts% (Typically 5%)
Mean Pore diameter 20 nm
Primary Particle Diameter 2-5 nm
lndex of Refraction 1.0-L.05
Coefficient of Thermal Expansions 2.0-4.0 x 106
L.t
Sounds Velocity 100 m,1sec.
having aerogel as an insulation materials and its life cost cycle assessment.
Task 2: Aerogel Characterization and Acquirins Commercial Products: Different commercial types of
silica aerogel products have been developed around the world, Some manufactures of silica aerogel and
product details are demonstrated in Table 2. The Pls will acquire aerogel blankets from at least three
certified manufacturers after consulting with the project manager. The thermal characteristics of the
individual sheets (thermal conductivity, thermal diffusivity and specific heat capacity) will be investigated
through the manufacturers and available data.
Task 3: Field Data Collection: To evaluate the effectiveness of the proposed innovative insulating material,
it is important to evaluate their in-situ applications, an actual building {Albertson building, built 2002 as
shown in Figure 2) at the University of ldaho will be chosen for the study. Thermocouples and heat flux
sensors will be attached to the building walls/panels after retrofitting multiple locations with Aerogel
blankets to collect real data to be used for the simulation verifications (task 4). The heat transfer
properties of the insulated walls will be compared to the un-insulated walls in the same building.
Task 4: Modelins and Simulation (Case Studvl
ln this task, two different types of modeling will be performed as follows: The buildingl s outside envelope
interacts with the external environment; external air temperature and solar radiation influence the
Dielectric Constant
Temperature Range -190 octo 1200 oC
3lPage
outside surface temperatures of roofs and walls, and the heat flux through the envelope is affected by
fluctuations during the day period. Sketch up and Energy P/us are the tools which will be used for modeling
and simulation the case study (Albertson building).
Table 2: Manufactures of Silica Aerosel blankets
Company Product Applications
Cabot Nanogel Architectural daylighting
lndustrial applications like
refineries, petrochemical and
gas process Fire protection in
below-ambient applications in
the oil and gas processing
industry
Marketech Aerogel Atomic particle detectors, super
insulation for aerospace
applications, insulate the Mars
rover Figure 1: Aerogel blankets
The robustness of the software lead to simulate various environmental conditions and evaluate the
impact of aerogels in heat loss of the building in different seasons. ln this context, it is important to carry
out deep investigation of dealing with optimizing layers' configuration in exterior walls. Considering old
buildings, it can be useful to analyze their thermal behavior before and after refurbishment actions, such
as using aerogel-incorporated renders. The Albertson building on the University of ldaho campus will be
used as case study for modeling and simulating the heat transfer envelope. The key parameters
considered in the simulation are shown in Table 3.
Task4: Cost Analvsis: The cost per unit volume of aerogels in
2020 may reduce to one-half of its cost in 2009 [9]. This cost
reduction, coupled with savings in floor space, makes aerogels
a more attractive thermal insulation option, especially for
retrofits [9J. Life cycle cost assessment will be conducted for the Figure 2: Albertson building, University
proposed system. of ldaho
Task 5: Environmental lmpact: Reduction of heat loss results in reduction of energy for_cooling and
heating. Thisdirectionleadstoreductionof COzemissionintotheairandimprovingtheairquality. lnthis
study, COa reduction over using Aerogel blankets will be estimated.
POTENTIAL MARKET PATH: The constructability of those blankets is very affordable and that could be
performed by stapling the blankets of aerogel on various configurations of external walls. The annual heat
loss is expected to significantly decreaseby 5A% compared to the currently used insulation materials.
Aspen
Aerogel
Pyrogelo
XT
Pyrogelo
XTF
Cryogelo Z
4lP*ge
Table 3: Key parameters
lf the technology appears to become feasible and in what
time horizon, then recommendations for developing it further
will be made and lt will be applicable to various buildings at
the University of ldaho as a first step to transfer this knowledge.
lf that shows promise, engaging energy development resources,
for example, through US Department of Energy or State innovation
and entrepreneurial funding would follow. The results may
w.ll
S"(tion
Concaete
Timbar
Matonry
ln.ulatlon
Locadon
Extfrior.
San d wrch
lnt!rror
Extsrior
Sa-ndwrch.
.llig',ol . ..
Exlerior
.5aDdwich. .lntcrior
xay Panm!tc6
. inrriutton
thickness
. El.nket
source
r Temperature
range (-100c
to 60oc)
. Blanket
typci {thr..
tYpes al
lcrjt will be
re6t.d).
Currant Exteriorlniulation Stndwtctr
lnterior
also suggest commercially available technologies that can instead be implemented on the system. ln that
case, an implementation plan for moving forward to benefit the system ratepayers will be suggested.
CRITERIA FOR MEASURING SUCCESS: The deliverables for success in this project will include the following:
1.. Report comparing all current wall insulations to the proposed insulation system using Aerogel for
providing energy savings and more efficient cooling/heating systems.
2. Report on the Analysis and testing of the energy saving and recycling of real buildings.
3. Report on Life Cost Analysis to produce efficient wall insulation system for the coming decades.
BUDGET:
Item Cost
Faculty salarieslsummer appointments
Ahmed lbrahim 4,822.24
Benhaz Rezaie
Brian Johnson
5064.83
2999.73
Graduate salaries (academic year)15,600
Grad salaries (summer)4,404
lH Part-time or Summer Students 2,640
Faculty fringe {summer)3,337.68
Full-Time Student academic 374.4
Student summer fringe 105.6
lH (part-time student) fringe 63.36
Subtotal (salaries & fringe)39,407.84
12,000Materials and Testing cost
Travel 400
Full-time grad student fees 9,044
Grad student insurance 1,866.36
Subtotal 23,310.36
Total Direct Costs 62,718.20
lndirect Costs 26,059.34
TOTAL 88,777.54
Salaries: Ahmed lbrahim, Behnaz Rezaie, and Brian Johnson will provide advise to the undergraduate and
graduate students. lbrahim will also teach and identify literature as well administrative coordinator.
lbrahim requests 80 hours of summer salary. Rezaie requests 80 hours of summer salary and Brian
5lPage
Johnson reguests 36 hours of summer salary. Fringe benefits for faculty is 75.9%. One graduate student
will work as a research assistant during the academic year of 2017-2018. The student will be employed
780 hours/S20 per hour during the academic year and 440 hours during summer 2Ot8/520 per hour. The
student will be involved in collecting field data, data analysis, and develop and test simulation. One
undergraduate student will be employed for 11weeksl2O hours per week on a rate of $12 during summer
2018. Student benefits: Student fringe benefit rate is 2.4%in the academicyear and summer. Tuition
and insurance: Academic year graduate student in-state tuition per student at the rate of 54522 per
semester and health insurance at the rate of SfAg6.ag. Materials: The team requests S1Z,OOO for
thermocouples, heat flux sensors and to cover the cost of Aerogel blankets. Any money not spent on
materials may be spent as student or faculty salaries and benefits. Travel: Two trips to Avista in Spokane
to present results and to consult with Avista engineers and management. F&A / Overhead: Assessed at
the rate of 5O3% of project direct costs except tuition.
PROPOSAT EXCEPTIONS TO THIS RFP (IF ANY):
Per section 5.2 of the RFP, the University has described exceptions to RFP requirements and conditions
in the letter dated 4/4h7 and included with Appendix A.
REFERENCES
1. LLP, S. D. C.,2Ol2.lnvestment Opportunity. [Online]
2. Avai lab le at: http :/lwww.sdcl-i b.com/what-we-do/energy-efficiency-
projectsinvestments/investment-opportun ity, html
3. Weina.Zhang, 2005. Preparation and characterization of hydrophobic silica aerogels at ambient
pressure, Changchun: Changchun University ofScience and Technology
4. http://www.cabot-corp.com/.
5. M. A. B.Meador, B.N.Nguyen, H.Guo et al., "Aerogels: thinner, lighter, stronger," 2011,
htt p://www. nasa. gov/topicsltech nology/ featu res/aerogels.htm l.
5. Aspen Aerogels, "lnsulated building materials," US Patent 7771609,2070.
7. Aspen Aerogels, "lnsulated building materials," US Patent 8277676,2072.
8. http:l/www.aerogel.com/.
9. Chotangada Gautham Somana, (2017), Evaluation of Aerogel Composite lnsulations by
Characterization and Experimental Methods, MS Thesis, College of Engineering Bangalore, lndia,
20L2.
6lPage
APPENDIX C: FACILIT]ES AND EQUIPMENT
Laboratorv:
The Pls has a lab equipped and full operational control and data logger system (Delphin Expert Logger
200) that can handle 32 sensors (strain gages, thermocouples and heat flux sensors) at a time. The system
is portable and will be used in the field measurements anticipated during the project.
Computers and Software:
The Pls of the proposed project have a personal PC in their offices. All the project personnel have access
to the departmental computer lab. All computers have a mix of licensed software and freeware available.
Through the current projects with Avista, the Pl's have access to a version of Energy Plus, In addition, the
Pl's have the full license for PowerTech Lab's DSATools software that can perform large scale power and
Heat system simulations. Therefore, all the project personnel, including students, will be able to use the
aforementioned software for simulations.
Project personnel also have access to newly purchased adaptive computational server "Big STEM"
sponsored by NSF award t229766: Hewlett Packard DL 980, 160 Cores CPU, 4 TB RAM, and 15 TB disk,
Linux OS. The machine supports up to 40 separate concurrent experiments/simulations each with 2
processor cores and 50 GB of memory, parallel computation across any number of processor cores. lt can
manage large-scale simulations across hundreds of virtual machines each running small portions of a
parallel algorithm.
7lPage
APPENDIX D: BIOGRAPHICAT SKETCHES
Ahmed A Ibrahim, Ph.D., P.E.
875 Perimeter Dr. MS 1022, Departmcnt of CivilEnginccring
Unir.crsity of ldaho, Moscorv,lD t138344
aibrah im(a.tu i daho. e d u
P rofcssional Prcparation
Appointments
P rofcrssional Registration
Registered Professional Engineer: State of Michigan
Registered Professional Engineer: State of ldaho
Selscted Publications
a) Journals1. lbrahim A., and Salim H., "Damage Model of Reinforced Concrete Slabs under Near-Field
Blast." lnternational Journal of Protective Structures - Volume 2 . Number 3 (2011),
pp. 31 5-332. DOI : 1 0. 1 260t2041 -4196.2.3. 31 5.2. lbrahim A., Salim H., and Shehab El-din H., "Moment Coefficients for Design of Waffle
Slabs with and without Openings." Engineering Structures, Vol. 33 (201 1), pp.2644-2652.
DOI :'t 0. 1 0 1 6lj. engstruct.20 1 1 .05.01 2.3. lbrahim A., and Salim, H. (2012) "Strengthening of Concrete Box Girder Bridges under
Close-in Detonations', Journal of Civil Engineering and Architecture. June 2012, Volume
6, No.6, pp.699-706. ISSN 1934-73594. lbrahim A., and Salim H. {2012), "Finite Element Analysis of Reinforced Concrete Bridges
under Close-ln Detonations", ASCE journal of Performance of Constructed Facilities, Vol.
27, No.6. pp.:774-784. DOI: 10.1061/ (ASCE) CF.1943-5509.0000360.
5. El-Chabib, lbrahim A., (2013), "The Performance of Ultra-Strength Flowable Concrete
Made with Binary, Ternary, and Quaternary Binder in Hot Climate', Construction and
Building Malerials,47,pp.245-253. DOI: 10.1016/j.conbuildmat.2013.05.062.
6. Lindquist, W., lbrahim, A., Tung, Y'., Motaleb, M., Tobias, D., and Hindi, R., "Distortion-
lnduced Fatigue Cracking in a Seismically Retrofitted Steel Bridge-Case Study", ASCE
Joumal of Performance of Constructed Facilities, DOI: 10.1061/(ASCE)CF.1943-
5509.0000783.
7 . West, J. Ibrahim, A., and Hindi, R. (20'16), "Analytical compressive stress-strain model for
high-strength eoncrete confined with cross-spirals'. Engineering Structures 113, 362-370.
DOI : 1 0. 1 01 6/j.engstruct.201 6.01.049.
Graduate Students. Currently supervising (6) MS students and (2) Ph.D. students at the
University of ldaho.
8lPage
Behnaz (Beth) Rezaie
Assistant Professor, Department of Mechanical Enginecring
Collcgc of Engineering, Univcrsitv of Idaho
PhD, Univcrsity of Ontario Institute of Technologv, Oshawa, ON. Canada, 2013, Mechanical Engincering.
MASc, University of Ontario lnstitute of Technology, Oshawa. ON, Canadq 2009, Mcchanical
Engineering,
l\IASc, Luleri' Univcrsity of Technology, Luleri, Norrbotten County" Sweden, 2002, Industrial
Management.
BSc, lran Science and Technology University, Tehran, Tehran, Iran, I992. Mechanical Enginccring
Licenscs: Registcred Engineer u'ith Professional Enginecrs Ontario, Canada.
EXPERIENCE:
Academic Appointments:
Assistant Professor, University of Idaho, USA Aug 2015- Prescnl
Lccturer. Univcrsity of Ontario Institute of Technology (UOIT), Canada Jan 2014- May 2015
I ndustrial Experience:
Manufacturing Enginccr, Johnson Control (JCI), Canada Jan 2007- Oct 2007
Quality Enginccr, Johnson Control (JCI), Canada Feb 2006- Dec 2007
Quality Process Enginccr, DBG, Canada 2003- 2006
Manager of Communication & Rclationship of the Company & Univcrsity, Mega Motors Co.l999-2000
Quality Laboratories Manager, Mega Motors Co. (Ticr l), Iran 1996- 2000
R&D Engineer, IKCO Research Ccntre, Iran 1995- 1996
Production Managcr, FKM Co., Iran 1992- 1999
R & D Engineer (part time), Profcssor Hcssaby Research Ccntre, Iran 1992- 2000
Selected Peer Revieu,ed Journol Papers. Compton, M., Rezaie, 8.,2017, Enviro-exergy sustainability analysis of boilcr cvolution in district
encrgy system, Encrgy, http:l1dx.doi.org/10. I 0l 6lj.ene rgy.20l 6. I 1 . 1 39.
r Lake, A.. Rezaie, B., Beyerlcin, S.,20 17, Revicw of district heating and cooling systcms for a
sustainablc future, Renewable and Sustainable Encrgy Reviews, 67:417425.
o Rezaic, B., Reddy, BV. Rosen, MA., 2017, Thcrmodynamic optimization in thc design ol sensiblc
thermal energy stor&ges, International Journal of Energy Research, 4l (l), 3948.
r Rezaie, B., Javan, S., Mohammadi, V., Ahmadi, P.,2016, Performance Assessment and Optimization
of a Combincd Cooling, Heating and Porvcr (CCHP) System for Residential Application using Low
Gradc Heat ol an lnternal Conrbustion Engine, Currenl Alternative Encrgy I , I - I 9.. Rczaic, 8., Reddy, BV. Roscn, MA., 2015, Exergy analysis of thcrmal cncrgy storage in a district
cnergy application, Renewable Encrgy,74: 848-854.
o Rezaie, B., Rcddy, BV. Rosen, MA.,2014, Energy Analysis olThermal Energy Storagcs with Grid
Confi gurations, Applied Energ.v, I 17 :5 4-6 I .o Rczaic, B.. Reddy, BV. Rosen, MA.. 2014, An Enviro-Economic Function lor Assessing Encrgy
Resources for District Energy Systems, Energy, 70: I 59- 164.
o Rczaie, 8., Esmailzadch, E., Dincer, I., 2013, Energy options for rcsidential buildings asscssmcnt,
Energy Conversion and Management 65: 637-646.
o Rezaic, B., Rosen, M.A., 2012. District heating and cooling: Rcvicw of tcchnology and potential
enhancemcnts. Applied Energy, 93:2-10. (Highly Cited Paper, Au,ard by Applied Energ,-)r Rszaic,8., Esmailzadch, E., Dincer, I.,2011, Renewablc encrgy options hr buildings: Case studics,
Encrgy and Building 43:56-65.
9lPage
Brian K. Johnson, Ph.D., P.E.
Professor of Electrical Engineering
Schweitzer Engineering Laboratories Endowed Chair in Power Engineering
University of ldaho, GJL 201, Moscow, ldaho 83844-1023
[phone]; [e-mail]
Professional Preparation
University of Wisconsin-Madison, Madison, Wl Electrical Engineering BSEE, 1987
University of Wisconsin-Madison, Madison, Wl Electrical Engineering MSEE, 1989
University of Wisconsin-Madison, Madison, Wl Electrical Engineering PhD, 1992
Appointments
2004-present: Professor Electrical Engineering, University of ldaho
2A06-2A72: Chair, Department of Electrical and Computer Engineering
1997-2O04: Associate Professor, Electrical Engineering, University of ldaho
1992-7997: Assistant Professor, Electrical Engineering, University of ldaho
Professiona I Registration:
Registered Professional Engineer (ldaho #8368)
Recent Publications
1. Taylor, D.1., J.D. Law, B.K. Johnson, and N. Fischer. "Single-Phase Transformer lnrush Current
Reduction Using Prefluxing," IEEE Transoctions on Power Delivery, Yol.27 , No. 1, January 2012,
pp.245-252.
2. K. Eshghi, B.K. Johnson, C.G. Rieger, "Power System Protection and Resilient Metrics"
Proceedings of the 2075 Resilience Week, Philadelphia, PA, August 18-20, 2015
3. R. Jain, B. Johnson, H. Hess, "Performance of Line Protection and Supervisory Elements for
Doubly Fed Wind Turbines" Proceedings of the 2075 IEEE Power ond Energy Society Generol
Meeting, Denver, Colorado, July 27-31, 2015
4. A. Guzm5n, V. Skendzic, M. V. Mynam, S. Marx, B. K. Johnson, 'Traveling Wave Fault Location
Experience at Bonneville Power Administration," Proceedings of the lnternational Conference on
Power Systems Transients (|PST2}15), Dubrovnik, Croatia, July 15-18, 2015.
5. B. K. Johnson, S. Jadid, "Synchrophasors for Validation of Distance Relay Settings: Real Time
Digital Simulation and Field Results," Proceedings of the lnternotionql Conference on Power
Systems Transients (|PSTZ015), Dubrovnik, Croatia, July 15-18, 2015.
5. H. Li, G. Parker, B.K. Johnson, J.D. Law, K. Morse, D.F. Elger, "Modeling and Simulation of a High-
Head Pumped Hydro System," 2014 lEfE Tronsmission ond Distribution Conference ond
Exposition, April 2014.
7. Y.Xia,B.K.Johnson,H.Xia,N.Fischer,"ApplicationofModernTechniquesforDetecting
Subsynchronous Oscillations in Power Systems." Proceedings of the 2073 IEEE Power ond Energy
Society General Meeting, Vancouver Canada, July 21-25, 2013
8. Y. Xia, B.K. Johnson, N. Fischer, H. Xia, "A Comparison of Different Signal Selection Options and
SignalProcessingTechniquesforSubsynchronousResonanceDetection," Proceedingsofthe
lnternational Conference on Power Systems Tronsients (lPST2013), Vancouver, Canada July 18-
20,2013.
9. M.P. Bahrman and B.K. Johnson, "The ABCs of HVDC Transmission Technologies," IEEE Power
ond Energy. Vol. 5, No. 2, pp.32-44, March-April 2007..
Rclated Research Projects.
l. B.K. Johnson and J. Alves-Foss, "TWC: Small: Securing Smart Power Grids Under Data
l0 lPage
Measurement Cyber Threats", Syracuse University (subcontract of NSF funding). August 16,
201S-August 15, 2018, S210,696.2. B.K. Johnson and H.L. Hess, "Smart Wires for lncreasing Transmission and Distribution
Efficiency," Avista Corporation, August 23,2015 - August 22,2OL6,575,O44
3. H.L. Hess and B.K. Johnson, "Critical Load Serving Capability by Optimizing Microgrid Operation,"
Avista Corporation, Oct 1-2015 * Sept 30, 2016, S79,855.4. B.K. Johnson, "Online Synchronous Machine Parameter ldentification," Schwcitzcr Enginccring
Laboratories, Inc. August l, 2014-July 31, 2016. $ 155,037.
5. B.K. Johnson, and H.L. Hcss, "Modcling and Dcsign Options for an All Superconducting
Shipboard Electric Power Architecture," Office of Naval Rcscarch, October 2013-Scptcmber.
2015, $56.894(r. Johnson, B.K, J.D. Law and D.F. Elger, "Rcnewable Energy Balancing," Shell Energy North
America, June 1 [, 2012-Much 31, 2013, $75,000.
7. Johnson, B.K. and J.D. Law. "Subsynchronous Resonancc Risk Assessmcnt and
Countcnneasures," Laboratory for Applied Scicntific Rcsearch (subcontract from Schwcitz.cr
Engineering Laboratories, Inc.), IMarch 3 1, 20 1 2-January 3 1, 20 1 3, $35,88 1 .
8. Johnson, B.K. and Hess, [I.L, "Modcling of Harmonic Injections and Their Impacts." Idaho
Porvcr Corporation. $48.674, Junc l, 2006-August 15,2007.
11 lPaee
APPENDIX D
Boise State University Agreement
li,lrsra #
TASKORDERNO. OOI
TO SPONSORED RESEARCH AND DEVELOPMENT MASTER PROJECT AGREEMENT
BETWEEN BOISE STATE UNIVERSITY AND AVISTA CORPORATION
THIS TASK ORDER NO. 001 ("Task Order") under that certain Sponsored Research and
Development Master Project Agreement Between Boise State University and Avista Corporation dated
effective as of September 1,2017 as amended from time to time ("Master Agreement'?) is made and
entered into by and between Boise State University, a State of Idaho institution of higher education
("University"), and Avista Corporation, a Washington corporation ("Sponsor"). Sponsor and
University may be collectively referred to herein as the "Parties" and individually as a "Part5/."
1) Task Order Scope of Work and Budget
University will perform the work in accordance with the Scope of Work, attached hereto and
incorporated herein as Exhibit A.
2) Task Order Term
This Task Order shall be effective commencing on September 1.2017 ("Task Order Effective
Date") and shall end on August 31.2018 unless terminated by a Party pursuant to the terms and
conditions of the Master Agreement ("Task Order Term").
3) Task Order Payment & Invoices
Sponsor shall pay University under this Task Order an amount not to exceed $90.574.00.
University will submit invoices for reimbursement pursuant to the terms and conditions of the
Master Agreement.
4) Miscellaneous
In the event of a conflict between the provisions of the Master Agreement and those of this Task
Order, the provisions of this Task Order shall control. No other terms and conditions of the Master
Agreement are hereby changed by this Task Order. The Master Agreement shall remain in full
force and effect, modified only by the terms and conditions of this Task Order, which terms and
conditions are expressly ratified and confirmed by the Parties. All terms initially capitalized herein
that are not otherwise defined herein shall have the meaning ascribed thereto in the Master
Agreement. This Task Order may be executed in counterparts, each of which shall be deemed an
original, but all of which together shall constitute one and the same Task Order. Facsimile
signatures and scanned and e-mailed copies of original signatures shall both be deemed to be
original signatures for all applicable purposes.
IN WITNESS WHEREOF, the Parties have executed this Task Order the day and year written below
when signed by the last of the Parties.
BOISE STATE UNIVERSITY:AVISTA CORPORATION:
TITLE:TITI,E
DATE:
BYBY
Boise State University - OSP 7792
Page I of7
DATE
EXHIBIT A
STATEMENT OF WORK
A DEMAI\II>SIDE APPROACH TO CONSERVATION BY VOLTAGE REGT'LATION
ENABLED BY RESIDENTIAL STATIC VAR COMPENSATORS
INSTITUTION Boise Sarc University
PRINCIPAL II{!'ESTIGATORS Said Ahmed-Zaid, PhD, PE and John Stubban, PhD, PE
PROJECT OBJECTN.'ES
Detelop the framework and simulation platforms to simulate, desigrr, and implement a laboratory
prototype of a Residential Static VAR Compensator (RSVC) cquipped with wo automatic control loops
for customer load voltage regulation and minimum load power consumption. Specific objectives are:
o Objective I: To simulatc. desiga, and implement a primary voltage regrrlation loop.
o Objectil-e II: To simulate, design" and irnplement a secondary power regulation loop as a
minimum power-point tracking (MPPT) Ioop.
o Objective III: To implement in hardware a functional laboratory protot)?e of an RSVC.
o Objective [V: To test the full RSVC prototype in a laboratory or home environment.
l,ko I ta Ch 4v'r <re, iN,5"4
AT}IOUNT R.EOUESTED $90,
RESOURCE COI!{}TITMENTS
PREVIOUS WORK
Year I of this project consistcd of a study model of a residential static var compensator (RSVC) for
regulating residsotial roltages. The studies from Year I showed that a single-phase RSVC offers a
significant potential for energy savings by voltage regulation and can bccomc a valuable tool in energy
conservation programs, especially during peak demand hours.
Year 2 of this project consisted of building an open loop control prototype of the RSVC device. The
irnplcmentation stratery involved a software centered approach that uscd an FPGA in coujunction with
Boise State University - OSP 7792
Page 2 of 7
Personnel "/" Effor-t Months Commcnts
Said Ahmed-Zaid t0%I Proiect oversight and production staff.
John Stubban ta%I Proiect oversight and production staff.
PhD Student t00%t2 PhD student and production stalf.
1
EXHIBIT A
STATEMENT OF WORK
bidirectional switches. Tbe bidirectional switches wcre constructed using unidirectional dcvices (IGBTs)
and diodes and cortrolled using a state machine to provide a smooth transition between states.
A second phase during Yczrr 2 of this project consisted in pcrforming time-series simulations over
rnultiple months using a model developed in OpenDSS for a downtown Spokane feedcr and a rural feeder
near lake Pend Oreille. The simulations showed that the dcployment of RSVCs could enhance CVR by
flattening the voltage profilc along the feeder. This allowed the voltage at the fccdcr head to be reduced
and maximized the benefits of CVR. A cost-benefit analysis was also performed to show that deployment
of thc RSVCs could be economically feasible.
During Year 3, the benefits of the mass deployment of RSVCs on the consumer side of distribution
networks wcre demonstrated through a number of proposed simulation studies. For example, this devicc
was show'n to be effective in multiple applications such as voltage optimization, conservatioo by voltage
regulation, power factor control, mitigation of power quality issues, etc.
PROJECT OVERVIEW
This rescarch proposes to pursuc the development of a residential static var compensator (RSVC) and to
develop a working laboratory RSVC prototypc equipped with two automatic control loops: One fast loop
rcgulating the customer load voltage to any desired reference voltage within Range A of ANSI C84.1
(120 V nominal plus or minus 5%) and a sccondary slower loop adjusting the referencc voltage to track
the point of minimum power consumption by the customer load. This approach to conservation by
voltage regulation (CVR) has the merit of adapting to the nature of thc customer load, which may or may
not decrease its energy consumption under a reduced voltage. This local approach to CVR is a radical
departure from current CVR stratcgics which have been in existcnce for over 30 years but have not been
widely adopted by electric utilities duc to high costs and technical challenges. The production and
commercialization of a local device which can regulate the customer load voltage and minimiz-c its power
consumption holds promise for implementing CVR easily and economically.
DET.{ILED TASKS
This purpose of this proposal is for the Boise State Universiry team to provide cnginccring research and
services for Year 4 of the ongoing project of a Residential Static VAR Corupensator (RSVC).
Boise State University - oSP 7792
Page 3 of7
2
EXHIBIT A
STATEMENT OF WORK
P ro i ec t Ma $a sem en I (Pe rfit rm ed t h ro u sh o u i prqi e cl )
Project rnanagem€nt will be performed by the principal investigator team of Dr. Ahmed-Zaid and
Dr. Stubban. Tbey will lead thc projed team to efficient and timely corrpletion of work through the
provisions of well planned wcll-scheduled and managed research and services such as: idcatifying risks,
anticipating problems, and quickly implementing plan resolutions to minimize impacts on thc project;
monitoring the effort expanded in the development of project deliverables; defining and implementing
specific requirements for project scheduling, staffing and quality; monitoring the project for deviations
from &e established scope; identifying and quantifying changes requested by Avista before proceeding
with the work.
Other tasks will include: conducting weckly internal project coordination rneetings to produce good
communications and clear understanding ofscope, schedules, budgets, technical issues, coordination of
interrelated tasks and near term deliverables; participating in biweekly conferencc calls with Avista to
update study and research progress: preparing an agenda for the conference call using the template
provided by Avista; ad&essing work completed during the current period and work expected to be
perforrned during the next period; highlighting items requiring resolution by Avista and the BSU rescarch
prqicct team.
Tusk 1: llSl'('l {lontrol Svstem L)esisn: L'oltase Reniation Loop ([*, Octoher 31. 201 7)
The objective of this task is to design and implcment the inner voliage regulation loop for an RSVC using
simple and detailcd MATLAB/Simulink models. Thc logical approach is to start with simple RSVC
models (for example, averaged power electronics rcdels) and design the voltage control loop using time
decoupling since the inner voltage regulation loop will be faster than the outer power minimization loop.
Once this control loop has been designed and its paramet€rs tuned to meet ceriain steady-state and
rransient specifications, the simulations will be rerun using a fully deailed model emulating the hardware
to be &signed as accurately as possible.
Tusk 2: llSl'C (lontrol Sl'stem Design: Pou,er Re%l$tion Loop (b1. Decemher 3I, 2017)
The objectivc of this task is to desigrr and implernent the outcr power regulation loop for an RSVC using
simple and detailed MATLAB/Simulink models previously developed during Task l. For this task, we
will first research currcrrt methods for desiping maximum power-point tracking (MPPT) algorithms and
hardware and select promising solutions for hardware implementation as a minimum power-point tracker
for the RSVC derice. Wc will irplement one such promising solution and simulate it in a
MATLAB/Simulink environment. This outer control u'ill be designcd as a slower loop than the inner
3
Boise State University - OSP 7792
Page 4 of 7
EXHIBIT A
STATEMENT OF WORK
voltage loop to build an inherent ti'ne decoupling benveen the two loops and avoid a possible system
interaction benveen the wo loops.
Task 3: I)esisn q{o.fimctional labaralory prototVte o-f an RSI;C. (br Mav l, }018)
This task will be performed in parallel with the simulation studies so that it can bc tested using thc control
parameters obtained from the simulation studies. An initial phase is to research suitable voltage and
currEnt sensors for the two contnol loops. The voltage regulation loop will only need a voltage lransducer
mcasuring a rcplica of the RSVC voltage which is also the crstomer load voltagc. The power loop, on the
other hand, will need the same voltage transducer as well as a current transducer monitoring the customer
load current. The two kansducer outputs will allorv the computatiou of the cycle-by-cycle average power
consumed by the customer load. An algorithm in the personal computer (MATLABiSimulink/dSPACE)
or in a microconkoller (FSoC5 from Cypress) will determine how to slorvly change the reference vohage
for minimum power consumption by the customer load in Range A of ANSI Standard C84.1.
Task 1: 'l eslinq of an RSI"C proton*De in a luboralon: or home enfironment (bv Ateust I , 20 I B)
Once a rvorking prototype has been constructed and shown to be fully functional, it will be subjected to a
scrics of cxtensive tests in the laboratory or in a home environment if desired by Avista. The prototype
device is being built for a 120 V standard outlet so that it can be tested on a home appliance rated at that
voltage.
Tas* 5: I:inal draft Reoori lbt'Attsust l. 2018)
Corrpile a draft report to include an executive summary, methodology, dat4 assurytions, analysis and
conclusions. Prepare and submit the draft report to Avista by email or a secure file share site. The draft
report will bc delivered to Avista for their rcview and comments.
Task 6: Deli,er linal renort and preseni results at Avisla headquarters (b], August 3l,. 2018)
Prepare and submit the final repod to incorporate Avista commeots on the draft reporL Prepare a
presentation to be given onsite at Avish headquarters. Deliver the final rcport to Avista via email or a
secure file sharc site.
POTENTTAL II{ARI(ET PATH
The porential market path of the residential static var compensator (RSVC) being built and simulated in
this project is similar to that ofother shunt-connectcd, reactive-injection-bascd devices currently being
deployed by somc utilitics. An RSVC prototype is being tcsted iu hardware at Boise State University for a
Boise State University - OSP 7792
Page 5 of 7
4
EXHIBIT A
STATEMENT OF WORK
voltage control application (Conservatioo by Voltage Regutation) on the consumer side of the disribution
feeder. The single-phase RSVC device has the adlantage oyer conventional shunt capacitors of being able
to operate in a capacitive or inductive rcde without gencrating large undesirable harmonics which are
typical of conventional thyrisor-based SVCs currently deployed, The RSVC uses a novel pulse width
modulation (PWM) scheme to create the variable var compensation, which pushes the RSVC harmonics
into a higher freguency band. This smart device can be used in multiple applications such as continuous
voltage coqtrol ar a load point, power factor control, mitigation of powcr quality issues, etc. Thc benefrs
of the mass deployment of RSVCs on the consumer side of distribution networks has been demonstrated
through a number of simulation studics in previous years of this project. The new RSVC device has the
potential to disrupt other competitor devices on three fronts: cost, power quality, and smart-grid
applicability or compatibi lity.
CRITERIA FOR MEASURING SUCCESS
The criteria for measuring the success of thc devioe being constructed will depend on several factors:
l. The device will be tested at 120 V to determine if it has reasonable power loss relative to thc
customcr power saved (for example, if the device power loss is rougbly one order of mapitude
lower that the powcr saved).
2. The device has the ability to regulate the customer load voltage at a desired reference level.
3. The device has the ability to minimize the customer power consumption by tracking the optimal
reference voltage.
4. The device docs not generate subsantial harmonics which might require filtering.
5. The prototype dcvice shall have a relativcly lower cost comparcd to existing competitivc devices
on the market even though they do operate using the same principles.
R.EFERENCES
[] Hua Jin, Gdza Go6s, and Luiz lopes. "An E{Iicient Switched-Reaclor-Based Static Var Compensator,"
IEEE fransaction on Industry Applications, Vol. 30, No. 4, pp. 998-1005, JulylAugust 1994.
[2] Jawad Faiz and Behzad Siahkolah. Electronic Tap{hanger for Distribution Transformers. Springer-
Vertag 201l.
Boise State University - OSP 7792
Page 6 of 7
5
EXHIBIT B
Budget
Dr. Said Ahmed-Zaid
Avista Budget - Task Order 001
911t17-8131t18
Budqet Cateoories Effort Mths 12 months Tota!
Salaries
Pl Dr. Said Ahmed-Zaid Summer 0.85 $8,911 $8,911
Co-PlJohn Stubban (Visiting Asst Prof) Summer 0.85 $9,728 $9,728
PhD Graduate Research Assistant 12.O0 $26,000 $26,000
$44,639 $44,639
Fringe Benefits
Pl Dr. Said Ahmed-Zaid Summer
olto
$3,030 $3,03034%
Co-Pl John Stubban (Visiting Asst Prof) Summer 33%$3,210 $3,210
PhD Graduate Research Assistant 7%$1,820 $1,820 current
GRA Health lnsurance $2.959 $2,959 $ 2,818
$11,0lg $1l,0l g
o&E
Parts & Supplies for Building RSVC
Prototype $1,000 $1,000
Equipment Under $5K: Computer &
Peripherals $
Recharge/Analysis cost $
Publication/Dissemination $
TotalO&E $1,000 $1,000
Travel
Travel to present research results $1.500 $1,500
Total Travel $1,500 $1,500
Student Costs current
Graduate Student Fee Remission AY 2017-
2018 $8,862
$
$8,862
$
$8,4!0
Total Student Costs ()8,862 $8,862
Total Direct Costs $67,O20 $67,O20
Base for lndirect Calculation $58,'158 $58,'158
lndirect Costs (F&A) MTDC On-Campus
Research 40.5%$23,554 $23,554
Total Costs $90,574 $90,574
Boise State University - OSP'7'792
PageT of7
I I +
I
I I
I
I
I I I
Aiwsra
APPENDIX E
Final Report: RSVC Year 4
Confidentia!
APPENDIX F
Final Report: Aerogel Phase 1
ft,,tsra X
Universityotldaho AHTETfr
College of Engineering
Aerogel Insulation System: An Innovative Energy
Efficient Thermal Wall
Project Duration: 12 months Project Cost: Total Funding $88,777
OBJECTIVE
In 2015, about 4Oo/o of the total U.S. energy
consumption was consumed in residential and
commercial buildings. The US government
promotes renovation of existing buildings tomake them meet minimum energy
performance requ irements.
The main objective of this project was to
investigate the thermal efficiency of Aerogel
insulation blankets as a new insulationmaterial for future implementation in
residential buildings' exterior walls. The
research tasks were conducted using
laboratory experiments, field measurements
and computer simulations. The computer
simulation tools included the EnergyPlus
software which is available to users throughthe U.S. Department of Energy and the
computational fluid dynamics (CFD) tool;
FLUENT in ANSYS Multiphysics. The field
measurements were collected from a room in
a real apartment where tests were before and
after the walls were insulated with the Aerogel
blankets. More details about all the project
tasks will be discussed later in this report.
BUSINESS VALUE
Energy sustainability is a crucial issue for
humanity's development in modern era, which
can significantly impact future quality of life
and the environment. The industry is moving
towards the construction of sustainable,
energy efficient buildings. The outcomes of the
current research will be applied to help Avista
customers save energy, reducing the need for
natural gas and electricity. The Aerogel
blankets will potentially be used in retrofitting
existing structures to improve efficiency and asa new well-developed material for new
construction.
It is anticipated that the results will
demonstrate that use of Aerogel reduces the
heat transfer across building wall envelopes
and therefore reduce the annual heat loss
compared to the currently used insulation
materials. In addition, a cost analysis was
performed and compared to the performance
of conventional insulation material.
BAGKGROUND
Aerogel, also called solid smoke, is a synthetic
porous material with remarkable properties.
Aerogel is made up of dried gels with a very
high porosity. It was discovered in the early
1930s. Aerogel molecules do not decompose at
high temperatures and do not release harmful
gases. Even at B00oC, the thermal conductivityof Aerogel is only 43 mW/(m. K). Moreinformation could be found in
https : //www. aeroqel, com/ rese!l'Eeslcommo
n/ u se rf i I es/fi I e/ Da ta %o 2 0 S h eets/ S pa ce I oft-
Eu ropea n-Datasheet-EN. pdf
SCOPE
Acceptable insulation materials need to
achieve as low a thermal conductivity as
possible, enabling a high thermal resistance as
well as a low thermaltransmittance. The scope
of this project is mainly focused on evaluating
the ability of the Aerogel blankets to save
energy through this study which is broken
down as follows:
Task 1: Literature Survey
Provide a report with an up-to-date summary
of studies on the characterization of Aerogel,
along with a preliminary investigation of its
implementation as a super insulator.
Task 2: Aerogel Acquisition
Acquire aerogel material for use in testing and
research supplies to be used in the
investigation of the thermal characteristics of
wall insulation.
Task 3: Data Collection
Build a test cell and perform testing and
measurements to investigate Aerogel
performance. Then insulate the walls of an
apartment with the aerogel blankets and
report the heat flux and temperature decay
profile across the insulated walls during typical
winter days in Moscow, ID.
Task 4: Modeling and Simulation
Conduct a finite element analysis using the
ANSYS software computational fluid dynamics
(CFD) to validate the aerogel thermal
conductivity compared to the predicted inner
wall temperature with the measurements
performed in Task 3. The goal of this task is to
perform parametric analysis during Phase II of
the project. This task also includes the
EnergyPlus software simulation of the
performance of a whole residential apartment
with walls insulated with Aerogel.
Task 5: Cost Analysis
The aim from this task is to determine the cost
savings when Aerogel is used as an insulation
material compared to the existing insulation.
DELIVERABLES
The main deliverables of this project will be a
final report that includes:
1. A description of the methods used in
the laboratory and field data collection, the
computer simulations, and an analysis of the
results showing the exact thermal conductivity
of the Aerogel blankets.
2. Cost analysis to compare the existing
cost of the current insulation material with the
anticipated cost of the walls insulated with one
and/or two layers of the Aerogel.
PROJECT TEAM
SCHEDULE
I. RESEARCH MOTIVATION
The chief objective of this research is
developing a means to save energy for the
largest number of Avista customers. The
motivation for this project is to investigate the
feasibility of implementation of Aerogel
blankets as an alternative insulation material
for residential buildings to replace conventional
insulation such as fiber glass.
A long-term goal is to create a practical plan to
investigate and employ the Aerogel blankets
and identify the cost advantages to ratepayersof implementing this new technology as
measured through energy savings.
II. PROJEGT BACKGROU]TD
There are many commonly used insulation
materials such as mineral wool, expanded
polystyrene, extruded polystyrene, cellulose,cork, and polyurethane. For building
applications, vacuum insulation panel (VIP),
and gas-filled panels (GFP) are common
insulation materials. Reducing greenhouse gas
emissions is also a concern for design and
research on building energy savings [1].
Vacuum insulation panels (VIP) are open
porous core fumed silica enveloped with
metallized polymer laminated layers. The
thermal conductivity for VIP ranges from 3 to
4 mW. m-1.K-1. [2]. Despite the high cost ofvacuum insulation panels, they have
significant application for infrastructure
insulation [2] such as pipelines.
Gas filled panels (GFP) apply a gas that has
reduced thermal conductivity compared to air
Orqanization University of Idaho-Civil Engineerinq
Email [e-mail]
Name Shimul Hazra
Organization University of Idaho-Mechanical
Enoineerino
Email hazr0186@va nda ls. uida ho.edu
TASK TIilE
ALLOGATED
START
DATE
Ftl{sH
DATE
{Task 1: Literature
review){8/2017){1/2018}
{Task 2: Material
ourchasi no){1 Month}{LO/2017}{LL/2017}
{Task 3: Field Data
Collection){6 Months}{Lr/2077){s/2or8}
{Task 4: Simulation}{10 Months}{9/2017){7 /207A)
{Task 5: Cost
Analvsis){4 Months}{4/2Or8){8/2018}
{Task 6: Enviro
Imoact){4 Months}{7/20r8r.{1 1/2018}
PRtNGtPAL TNVESTIGATOR(S)
Name Ahmed Ibrahim
Organization University of Idaho-Civil Engineerinq
Contact #208 885 1328
Email aibrahim@u idaho.edu
Name Tao Xinq
Organization Un iversity of Idaho-Mechanical
Enqineerinq
Contact #208 885 9032
Email [e-mail]
Name Brian Johnson
Organization University of Idaho-Electrical
Enqineerinq
Contact #208 88s 6902
Email bioh [e-mail]
RESEARCH ASSISTA}ITS
Name Moammed Mudaqiq
The information contained in this document is proprietary and confldential.
{5 Months}
between two layers. Argon, krypton, and
xenon are typically used in Gas filled panels
(GFP) insulation system [2].
In a traditional insulation system, increased
thickness in the building envelop is useful.
However, very thick building envelops costsspace, reducing floor area, causing
architectural restrictions and requires
complicated building techniques [2].
Aerogel, is a synthetic porous material with
remarkable properties [3]. Aerogel was first
discovered in 1930, and different products
were developed to apply it. Aerogels are driedgels with a very high porosity. Aerogel
molecules do not decompose at high
temperatures and do not release harmful
gases. It is nontoxic, low flammable, air
permeable and lightweight [4]. Aerogels are
also used for batteries, nuclear waste storage,
absorbents and shock absorbers [4].
Aerogel has thermal conductivity range from
0.01-0.02 W.m-1. K-1 at ambient temperature,
resulting a well-balanced connection with low
solid skeleton conductivity, low gaseous
conductivity and low radiative infrared
transmission [5]. It is difficult to determine a
balanced relationship between different heat
transfer modes because all the modes are
tightly coupled to each other [6].
III. TECHNOLOGY UTILIZ,ED
ANSYS CFD and EnergyPlus are the softwaretools used in this project. Thermocouple
sensors and data acquisition system were used
in the laboratory and field data collection.
IV. ANALYSIS APPROAGH
An acceptable insulation material needs to
achieve as low a thermal conductivity as
possible, enabling a high thermal resistance as
well as a low thermal transmittance.
Spaceloft Aerogel blanket is the commercial
name of the product that has been used in this
project. Spaceloft has heat capacity of 1000
J/kg/K, a vapor permeability factor 4.7 Mu,porosity 92o/o, and a water absorption
coefficient of 0.025 Kg/m26r/z [7,8]. An
Aerogel blanket is referred to as fiber
reinforced silica aerogel. It is suitable for
insulating solid walls, floor, and roofs and has
been used in recent construction and in
refurbishing old buildings. Spaceloft reduces
the surface condensation and provides a highly
and effective technique for heat loss reduction
through floors and walls. Spaceloft is
manufactured in rolls with 5 mm or 10 mm
thick, 1450 mm wide and approximately 65 m2
per roll. Additionally, it does not depend on
vacuum or gases for insulation l7l.
The team purchased 8OO ftz of Aerogel
blankets. Each blanket has a 10mm thickness,
and was delivered in one roll as shown in
Figure 1. The team also purchased a Campbell
Scientific data logger, thermocouples and twoheat flux sensors to collect data from
residential building walls insulated by the
Aerogel.
The scope of this project is mainly focused on
evaluating the ability of the Aerogel to save
energy through a comprehensive study which
is broken
Fiqure 1: Aerogel Blankets
a) Data Gollection
The data has been collected through laboratory
testing and an actual field study using an
apartment.
One of the main goals of this project is to
validate the aerogel blankets thermal
conductivity and apply the results throughfinite element simulations. A small-scale
prototype was built first for verification under
a controlled setting and to derivation the heat
conductivity of the Aerogel. The prototype was
a 3.0 x 3.0 x 3.0 ft. wood frame as shown in
Figure 2a. The six walls of the cubical box were
covered with different insulation materials for
the purpose of collecting temperature datafrom three different scenarios. The first
scenario was where all of the walls were
covered with only Aerogel blankets, the second
case where all the six walls were covered with
only timber boards and the third case where all
walls were covered with a hybrid system
fhe information contained in this document is proprletary and confidential.
(Aerogel (inside)+ Wood (outside)). A
conventional space heater was positioned at
the center of the cubical volume and 19
thermocouples were mounted in different
places along the different faces of the cube as
shown in Figure 2a.
The sensors were mounted internally and
externally on the six faces as shown in Figure
2b. Figure 2b is a schematic diagram showing
the locations of sensors on one face (A). The
faces were given letters A to F with subscript
numbers referring to the location of the
thermocouples relative to each face. As an
example, A1 is the sensor located between the
wall center and the cube center, A2 is mounted
on the central point of the internal face of wall
and 43 is the sensor mounted on the central
point of the external face of the same wall.
In all of the studied cases, the heater was
turned on until the temperature reached
around 1200 F and then the heater was turned
off and data was recorded as the temperature
decayed until it reached room temperature.
This process was repeated 3 times for each
case (aerogel, wood, and aerogel+wood).
In addition to the laboratory experiments, field
data collection was conducted, where thirty
thermocouple sensors have been mounted to
the walls of one room of a student residential
apartment at the University of Idaho campus.
Sensors have been used to record data with
existing insulation and with Aerogel blankets.
Figure 3a shows a view of the apartment and
Figure 3b shows the thermocouples attached
to two walls of the room.
b) Modeling and Simulation
Computational fluid dynamics (CFD) simulation
has been used to simulate the cubical box built
with Aerogel insulation and EnergyPlus was
used to simulate the apaftment under testing.
Figure 2a: Small scale box with Aerogel Walls
o ril,ilil::"
il
h
\
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il
Cr6ffidtu-qiFa'lslheMhd[]dAtmrE
Figure 2b: Sensors locations across one of the
box walls.
The information contained in this document is prcprietary and confidential.
I
I
i
t&a
Figure 4 shows the temperature decay through
one of the scaled Aerogel box walls. It can be
seen that sensor A1 has the highest
temperature compared to the room
temperature. The inner (sensor A2) and the
outer (sensor A3) temperatures show a
significant difference. These temperature
data were used to validate the computer
simulation and verify the thermal conductivityof the Aerogel blankets (box wall). The
temperatures recorded by all of the sensors
decayed with various rates over time.
l/to
120
g1m
Figure 3: a) Exterior view of apartment, b)
thermocouple locations on the apartment
walls
V. RESULTS
a) Laboratory and Field Results
The information contained in this document is proprietary and confldential.
t0
50
iao
b
0
90 1@
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150 2m
Figure 4: Temperature profile across one of
the box walls.
CFD simulations were conducted on the small-
scale aerogel box using a constant outer wall
temperatur€, To = 2950 K and a specified innerwall temperature profile based on the
experimental data (shown in Figure 2b).
Further, the team also studied the effect ofusing different thermal conductivity
coefficients for the Aerogel (k =0.010, 0.014
and 0.018 W/m-K). Figure 5 shows the
comparison of inner wall temperature for all
the cases considered.
!t5
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Figure 5: Comparison of inner wall
temperatures between CFD and experimental
data
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-CFD
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-CFD
widr To profile and mw
inirial cmditiff (1F0.014)
-CtD
with To pIofile and mw
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The initial temperature fields have been
implemented in the CFD model using user-
defined functions. It was found that the best
match to the experimental data has been
achieved when k was 0.014 W/m-K. Figure 5
shows temperature distributions at different
instants from CFD simulations (specified to
profile, k=0.014). As seen in Figure 5, the
solution was initialized using two patches to
represent the measured inner wall
temperature and the temperature inside the
box when the heater was turned off . In
addition, a 3D temperature contour has been
developed as shown in Figure 6.
t
,,r.
average outside temperature was 47.6 oF,
while the inside initial room temperature was
530F. The team chose days with near typical
temperatures for data collection. The
experiment had three cases, a) walls without
Aerogel, b) walls with a single layer of Aerogel,
and c) walls with double layers of Aerogel. The
temperature collection was replicated three
times for each case and the average
temperatures was used in all the heat savings
calculations.
E:N 5d - apd ro ossd.
14-E E.E u.E
Ll.EEdFU2
s-E 19-E
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Figure 6: Temperature contour at different
instants (specified to profile, k=0.014 W/m-
K)
The second part of the data collection was from
an in-field scenario where Aerogel was used to
cover the walls, and the ceiling of one room in
a student apartment at the University of Idaho.
The data was collected from 30 thermocouple
sensors that were placed in one room. All of
the sensors have been mounted to cover all of
walls including the existing insulation. One ofthe sensors was extended outside the
apartment to measure the outside
temperature. Figure 7 shows a schematic with
all of the sensor locations across the walls, and
the ceiling.
After setting and mounting the sensors on the
walls and ceiling, the temperature data was
collected and plotted. The room was heated up
using two heaters until the room temperature
reached 72.6 oF, and then the two heaters
were turned off and the temperature was left
to decay till it reached a constant plateau. The
temperature-time history for all sensors were
recorded. Figure B shows a sample of the data
that was recorded from the south wall. The
Figure 7: Schematic diagram shows all the
locations of all sensors and heat fluxes.
Figure 8 shows how the outside temperature
fluctuated across the day and night and the
temperature-time history was used in the
calculation of the energy savings for all cases
considered.
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south wall
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The information contained in this document is proprietary and confidential.
I ,LI
South wall
a-t
b) Computer Simulations
The CFD was used to validate both the small-
scale laboratory experiment and the
temperature-time history measured from the
apartment case. This validation will enable the
investigators to extend a parametric study in
phase II of the project. Figure 9 shows a
comparison between the 2D CFD and the
temperature measured from the Aerogel box.
It can be seen that the CFD was able to predict
the temperature decay, however the CFD over-
predicted the initial temperature, but after
1000 seconds the CFD and the experimental
results were matched.
Tenrperature vs Time
Figure 11 shows the temperature contours and
velocity vectors at t= 1120 seconds during
heating and cooling of the room. The heating
source of 500 W was modeled for initial 5
minutes and the simulation was performed for
1.5 hours. Figure 12 shows a Preliminary
comparison between CFD and experiment for
inner south wall suface temperature. The final
temperature distribution results across the
room will be finalized in phase II of the project.
2.5
1.5
0.5
x
Figure 11: Temperature contour for the
monitored room.
^Experimental
*CFD
286.00
28s.00
284.00 0 1000 20(n 3m0
Time (seconds)
Figure 12: Preliminary Comparison between
CFD and experiment for inner south wall
surface temperature
The whole apartment was also modeled using
EnergyPlus which required inputs such as:
rThe R value of the current insulation, and the
thermal mass of the construction..The wall cross section construction details,
e.g. gypsum board, then insulation of 3.5
inches of fiber glass insulation, then brick
3.5
3
. fuFilfrdR$ . ShUH& BBS 2
125
310
}{!5
300
295
296
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Figure 9: Comparison between the predicted
inner wall temperature using CFD and
experimental measurements for a square
Aerogel box.
In addition, a 2D CFD model was built as
shown in Figure 10 for future investigation in
Phase IL Window
3.5
2.5
1.5
Door
Figure 10: Plan view of the apartment room
CFD model
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The information contained in this document is proprietary and confidenlial
l*-L;
L!9,\
veneer, etc. along with the year of
construction.. The exterior windows types with any thermal
information.
o The usage pattern of people that occupy the
unit. The team assumed 4 persons max..The schedule and set points for the
thermostat, especially for heating. There was
no cooling used in the summer for this
apartment under study. But if it is ever used,
the schedule (time) could be applied in the
simulation
.Daylighting, controls if any.
.Domestic hot water usage if a rough idea is
available.
The team tried to determine accurate inputs so
the simulations had reasonable results. The
results of the software were compared to the
energy bills obtained from Avista during the
calendar year for 20L7. Figure 13 shows thatthe EnergyPlus produced reasonable
comparison for when the apartment walls were
covered with one, two layers, and even three
layers of Aerogel.
Monthly Heating Energy Usage (Heating bill vs. EnergyPlus
Easline vs. EnergyPlus 1, 2, 3 layers of lnsulation)
apartment. The case with no aerogel has the
highest heat transfer over time while the wall
insulated with two layers of aerogel has the
lowest heat transfer, as expected. The team
used the temperature profiles collected from
the field to calculate the heat flux based on the
data collected from the apartment over a 24-
hour time frame. The k value was taken as0.014 w/m.k (determined from the lab
testing). The team also considered the
conservation of energy when two layers of
aerogel were used. The energy saving
analysis showed that one layer of aerogel
reduced the heat transfer by 43o/o and using
two layers reduced the heat transferred by
57olo compared to the control case (no aerogel)
as shown in Figure 15.
To forecast the energy saving for a full year,
the team has obtained the weather data for
2016 from the University of Idaho Integrated
Design Lab (IDL) in Boise, ID. The heat flux of
the three insulation cases has been calculated
and is shown in Figure 16. The results show
that one layer of Aerogel reduces the heat
transfer by 23o/o and two layers reduces the
heat transferred compared to the control case
(no aerogel).
90
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Figure 13: Heating energy consumption
comParison.
The results show that three layers of Aerogel
could reduce the energy consumption by about
10%o as shown in Figure 13. The investigators
found a potential drawback in the software
capabilities since the cost savings obtained
were less than expected given the very low
thermal conductivity of the Aerogel, which
should show more energy savings.
Vl. Energy Savings Analysis
Figures L4 shows the Energy (watt.)-time
history of all cases conducted at the
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Figure 14: Energy-time history of all cases
conducted at the apartment!0.o
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Figure 15: Heat Flux Comparisons between all
Aerogel Cases (24-hours forecast).
56.09
The information contained in this document is proprietary and confidential.
Figure 16: Heat Flux Comparisons between all
Aerogel Cases (one year forecast).
vtt. coNcLusloxs
The feasibility of using Aerogel blankets as a
super insulator to reduce heat fluxes has been
verified using small scale laboratory test, large
scale field test and high-fidelity computer
simulations. The following conclusions have
been drawn from the project tasks conducted:
1. The CFD was proven to be a promising tool
to identify the exact thermal conductivity (k)
using a small-scale laboratory test
2. The k value of one layer (0.40 inch) of
Aerogel blankets is 0.014 W/m-K.
3. CFD for an apartment/room needs to be
improved by improving assumptions and
approximations, which will be addressed in
Phase II of the project.
4. EnergyPlus has limitations for predicting the
real energy savings for buildings.
5. Based on theoretical analysis of
experimental measurements, one layer and
two layers of Aerogel reduced the energy
consumption by 43o/o and 680/o, respectively,
compared to the control case (no aerogel).
6. Looking over a period of one year, one layer
of aerogel reduces the heat transfer by 23o/o
and using two layers reduces the heat transfer
by 38o/ocompared to the control case (no
aerogel).
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References
GhaffarianHoseini A, Dahlan N, Berardi U,
GhaffarianHoseini A, Makaremi N.
Sustainable energy performances of green
buildings: a review of current theories,
implementations and challenges.
Renewable & Sustainable Energy Reviews
20t3,25:t-t7
Bjo rn Petter Jel le. Trad itiona l, state-of-the-
art and future and future thermal building
insulation materials and solutions
properties, requirements and possibilities.
Energy and Buildings. 43, 2Dtt, 2549-
2563.3. Husing N, Schubert U. Aerogels-airy
materials: chemistry, structure andproperties. Angewandte Chemie
International Edition. 1998, 2:22-45.4. Jelle B, Hynd A, Gustavsen A, Arasteh D,
Goudey H, Hart R. Fenestration of today
and tomorrow: A state-of-the-art review
and future research opportunities. Solar
Energy Materials & Solar Cells. 2012 ,9621-
28,5. Umbefto Berardi. Development of glazing
system with silica aerogel. Energy
Procedia. 78, 2015, 394-399.6. Baetens R, Jelle BP, Gustavsen A. Aerogel
insu lation for bu ilding a pplications: A
state-of-the-art review, Energy and
Buildings. z0lt, 43,761- 769.7. Faghri, Y. Zhang and J. Howell. Advanced
heat and mass transfer, Global Digital
Press, Columbia, Mo, USA, 2010.
8. J. Fricke. Thermal transport in porous
superinsulation in aerogel. J.Fricke, Ed,
vol6 of Springer Proceeding in Physics, pp.
94-t03, 1986.
2s(Irun
a[run
ts(Irul,
r@fl,
SmJp
ct
,
ot
0.q,
vllt.
1.
2
The information contained in this document is proprietary and confidential
APPENDIX G
Final Report: IDL Operative Temperatures
fr'rsra X
I NTTG RATT D
DESIGN tAB
University"f ldaho
Marune ING FoR ErrIcIeruCY BASED ON OPERATIVE
TrrupeneruREs
Pnorrcr RepoRr PRepRReo ron AvtsrR Urtt-trtrs
August 3L,2OL8
Prepared for:
Avista Utilities
Authors:
Damon Woods
Elizabeth Cooper
Neha Pokhrel
Ryker Belnap
A'l1vtsrA
Report Number: 1708_01
Prepored by:
University of ldaho lntegrated Design Lab I Boise
306 S 6th St. Boise, lD 83702 USA
www.uidaho.edu/idl
IDL Director:
Elizabeth Cooper
Authors:
Damon Woods
Elizabeth Cooper
Neha Pokhrel
Ryker Belnap
Prepared for:
Avista Utilities
Contract N umber: R-39872
Please cite this report as follows: Woods, D., Cooper, E., Pokhrel,
N., and Belnap, R. (2018). Monoging for Efficiency Based on
Operative Temperotures. (1708_01). University of ldaho
lntegrated Design Lab, Boise, lD.
DISCIAIMER
While the recommendations in this report have been reviewed for
technical accuracy and are believed to be reasonably accurate,
the findings are estimates and actual results may vary. All energy
savings and cost estimates included in the report are for
informational purposes only and are not to be construed as
design documents or as guarantees of energy or cost savings. The
user of this report, or any information contained in this report,
should independently evaluate any information, advice, or
direction provided in this report.
THE UNIVERSITY OF IDAHO MAKES NO REPRESENTATIONS,
EXTENDS NO WARRANTIES OF ANY KIND, EITHER EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF
MERCHANTABILITY, AND FITNESS FOR A PARTICULAR PURPOSE
WITH RESPEC'T TO THE INFORMATION, INCLUDING BUT NOT
LIMITED TO ANY RECOMMENDATIONS OR FINDINGS, CONTAINED
IN THIS REPORT. THE UNIVERSITY ADDITIONALLY DISCLAIMS ALL
OBLIGATIONS AND LIABILITIES ON THE PART OF UNIVERSITY FOR
DAMAGES, INCLUDING, BUT NOT LIMITED TO, DIRECT, INDIRECT,
SPECIAL AND CONSEQUENTIAL DAMAGES, ATTORNEYS' AND
EXPERTS', FEES AND COURT COSTS (EVEN lF THE UNIVERSITY HAS
BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES, FEES OR
cosTs), ARrslNG ouT oF oR lN coNNEcTloN wlrH THE
MANUFACTURE, USE OR SALE OF THE INFORMATION, RESULT(S),
pRoDUCr(S), SERVTCE(S)AND PROCESSES PROVIDED BY THE
UNIVERSITY, THE USER ASSUMES ALL RESPONSIBILITY AND
LIABILITY FOR LOSS OR DAMAGE CAUSED BY THE USE, SALE, OR
oTHER DTSPOS|T|ON BY THE USER OF PRODUCT(S), SERVICE(S), OR
(pRocEssES) TNcoRPoRATTNG OR MADE BY USE OF THIS REPORT,
INCLUDING BUT NOT LIMITED TO DAMAGES OF ANY KIND IN
CONNECTION WITH THIS REPORT OR THE INSTALLATION OF
RECOMMENDED MEASURES CONTAINED HEREIN.
TReLr or Corurrrurs
1. Acknowledgements..3
4
5
7
7
2. Executive Summary...
3. Research Motivation
4. Project Methods
4.1. Establishing a Baseline .........
4.2.2 Generating Solar lnformation from the data for other sites
4.2.3 Formatting the Weather Histories
5. Monitoring Results..
5. 1 Thermostat Reading Versus Other I nstruments ................
5.2 Energy Modeling Results - Winter
4.2 Energy Modeling Methods.... .................. 11
4.2.L Creating the Weather File L2
13
L7
19
23
25
275.3 Energy Modeling Results - Summer
6. Discussion and Future Work ......29
7. Budget Summary... .....................32
9. Appendix 36
lntegrated Design Lab I Boise 2
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
AcRoltyrus AN D ABBREVIATIoIIS
AHU
API
ASHRAE
EMS
EPW
HVAC
IDL
NOAA
NRSDB
PMV
PPD
RMSE
TMY
UI
Air Handling Unit
Application Program ming I nterface
American Society of Heating Refrigeration and Air conditioning Engineers
Energy Management Control System
Energy Plus Weather file
Heating, Ventilation and Air Conditioning
lntegrated Design Lab
National Oceanographic a nd Atmospheric Ad ministration
National Radiation Solar Data Base
Predicted Mean Vote
Percentage of Population Dissatisfied
Root Mean Squared Error
Typical Meteorologica I Yea r
University of ldaho
lntegrated Design Lab I Boise 3
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
This research was made possible through funding support from Avista Utilities via ldaho PUC Case Number
AVU-E-13-08. The research team expresses gratitude to Avista staff and project managers for their
support of this project. This project could not have happened without the coordination and help received
from facilities managers at each of the sites that was measured.
1. AcTTowLEDGEMENTS
lntegrated Design Lab I Boise 4
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
The University of ldaho - lntegrated Design Lab (Ul-lDL) monitored the humidity, surface
temperatures and air velocities at six different office sites. Data collected from these sites was used
to quantify the occupant comfort levels. Energy models were created for each of these sites. Weather
histories and solar models were used to generate simulations based on historical measurements. The
models were then adjusted to match the measured performance. Finally, the control settings in the
energy models were adjusted in order to contrast current performance with new control sequences
that provided better operational performance both in terms of comfort and energy.
The research team found that all offices surveyed dipped below the ASHRAE comfort guidelines
and were calculated to be uncomfortably cold. Typical thermostat settings were found to be 70oF for
heating and74"F for cooling with setbacks that varied by location. ln every case that was monitored,
instruments installed next to the thermostats recorded higher air temperatures than instruments
installed closer to the working areas of the office employees. Analysis of the data collected during the
winter indicated that increasing clothing levels helped, but did not alleviate predicted discomfort until
the heating setpoint was raised to72oF. Raising this setpoint may still come with an economic benefit
to customers due to increased productivity from a more comfortable workforce and may cut down
on the number of electric space heaters that were present in almost every location visited. Analysis
of the summer data showed that increasing the cooling setpoint to 75oF with a setback of 80'F
resulted in a cooling load reduction of t5-4O% for each site during the week observed. lncluding more
holistic metrics such as surface temperatures showed that raising setpoints during the summer would
both increase comfort and save energy for commercial offices in Avista Territory.
2. ExrcuTIVE SUMMARY
3. Rrsrencx Monvanont
lntegrated Design Lab I Boise 5
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
Controlling a building based on both surface and air temperatures could reduce energy
consumption and promote healthier buildings. Most buildings manage their heating or cooling based
solely on zone air temperature. Even when the thermostats are kept within a narrow band of 4oF,
occupant complaints persist [1]. A large factor of human comfort is being missed in conventional
thermostats: the inclusion of the mean radiant temperature. Many previous studies have established that
the temperatures of the surfaces surrounding us have a far greater impact on our comfort than the air
temperature [2]. lmagine a driver getting into a car that's been in the sun all day -the air conditioning
may be running, but the driver is still sweating for the first part of the drive until all the surfaces cool off.
A better comfort metric is the operative temperature which is a mix of air and surface temperatures.
While operative temperature is widely used for predicting human comfort, rarely is it directly used in
building controls.
Building operations could benefit greatly from operative temperature control. Operative
temperature control would allow for wider air temperature setpoints, thus saving energy each year. A
study by the Pacific Northwest National Lab estimated the following general energy savings: a 2oF
adjustment on both heating and cooling setpoints led to a fairly uniform HVAC energy savings of t2-20%
[3]. Nationwide, such savings would be equivalent to 370-615 trillion Btu saved annually [a]. This research
focus is decidedly narrower in scope: focusing purely on small commercial office buildings in the Pacific
Northwest, where HVAC energy is typically 35o/o of the annual load [4]. Research has shown that a
thermostat reset could result in totalannualenergy savings of 4-7% of annualenergy consumption per
building [5]. The adoption of wider setpoints based on operative temperatures by controls engineers and
consultants could quickly scale up and result in widespread savings. ln addition to energy savings, the
operative temperature control could dramatically enhance occupant comfort, thus making it an attractive
service to offer to clients.
lntegrated Design Lab I Boise 5
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
The simple shift in control from air temperature to operative temperature may have a dramatic
impact on energy consumption. Controlling for operative temperatures can be done with relatively simple
and inexpensive instruments: thermocouples. Expanding just the air cooling setpoint by 5oF can save up
to 27o/o of the total HVAC energy [5]. However, expanded setpoints are only viable if occupant comfort is
maintained. While establishing high cooling setpoints can save a lot of energy, if the occupant is
uncomfortable, they will either adjust the thermostat on their own or place considerable pressure on the
building operator to do so (thus nullifying any potential savings). Occupant satisfaction (or the lack
thereof) is the driving force behind thermostat adjustments. Up to S3g0 per employee per year in lost
productivity at work can be attributed to an office environment outside the bounds of ASHRAE 55's
comfort setpoints [5]. Therefore, any thermostat control scheme, operative or othenrrise, should focus on
comfort so that the setpoints are not immediately changed after they are implemented. An operative
thermostat control scheme focused on comfort has a far greater likelihood of remaining in place. Most
energy modeling misses this crucial interaction and instead assumes standard setpoints and setbacks.
That is why the first phase of this research was identifying typical setpoints at real buildings instead of
relying on ideal assumptions.
A control system that incorporates the operative temperature of a zone would allow for a wider
range of supply air temperatures and better meet the needs of occupants. The wider range of air
temperatures would reduce energy consumption and help to capitalize on operational features such as
natural ventilation, night-flush and optimized set-points. The outline of the work is to profile typical
setpoints found in operation, test alternative control methods, and estimate potential savings. No
occupant surveys were required for this study (opinions are highly variable and unique). lnstead, the
research relied on established thermal comfort criteria based on operative temperatures and humidity
readings taken at the site [7]. This study, leveraged extensive data collection paired with energy modeling
and comfort standards to inform efficient control schemes. The work provided key insights on how to best
lntegrated Design Lab I Boise 7
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
balance thermal comfort and energy savings for small commercial office buildings in the Paclfic
Northwest.
4.1 Establishing a Baseline
This work began with the research of typical thermostat settings for buildings in Avista territory.
The baseline was established through a mix of literature reviews and contact with controls engineers,
consultants, and building operators. While there are established guidelines for thermostat setpoints and
setbacks, the goal of this research phase was to uncover what the actual settings typically are. After
reaching out to several engineering firms, control contractors, and facility managers, the general
consensus was to keep buildings at a heating setpoint of 70'F and a cooling setpoint of 74"F. All who were
surveyed gave answers within one or two degrees of this range. One controls contractor noted that
thermostats can contain either a slight delay or overshoot so that the system will not commence operation
until the setpoint is exceeded by about 1'F. During the data collection phase, independent temperature
sensors were set next to the zone thermostats to verify these settings.
IDL coordinated with Avista to select six building sites for analysis as case studies. Each site was
an office - either a private office, open office, or cubicle. Some of these areas allowed employee access
to thermostat controls and some had locked thermostats that gave only facilities managers (not
employees) control over the setpoints. Each site was located in a climate shared with Avista Service
territory customers. The American Society of Heating Refrigeration and Air conditioning Engineers
(ASHRAE) partitions the US into eight climate zones that account for minimum/maximum temperatures
and humidity. All of Avista's service territory falls into either climate zone 58, or 5. A sketch overlaying
climate information onto the general Avista territory is shown in Figure 1.1
Pnorrcr Meruoos
lntegrated Design Lab I Boise 8
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
Figure 1.1 A general o'-itline of Avista's s*rvice terrltory ar-td the climate zones present in that area.
Due to IDL's location, several of the sites surveyed were located in Boise, which is also in climate
zone 5. The buildings surveyed ranged in size and had a diverse mix of HVAC systems. At each site, the
team chose one or more spaces inside the building to study in detail. Next, an array of data loggers were
installed in those spaces to record comfort metrics at the site throughout a work week. The comfort
metrics included the following: humidity, dry-bulb temperature, air velocity, and surface temperatures of
relevant surfaces (walls, windows, floors, ceilings, and desks). An image of one of the offices and the
instruments installed is shown in Figure 1.2 while a list of data collected and the instruments used is
provided in Table 1.
d AJene
AVISTA IERRIIORY
WASHINGTON
OREGON IDAHO
lnteg.ated Design Lab I Boise 9
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
Figure 1.2 The temperature and velocity sensorr installed at one of the offices surveyed.
The research team also gathered thermostat readings and energy consumption data from the
energy management system (EMS) if it was possible. The IDL team only used the EMS data at one site and
this data collection was through a secondary program called SkySpark. A list of the sites selected and their
HVAC systems is shown in Figure 1.1. The dates of data collection for each site are listed in the Appendix.
Measurement Tool
lndoor Dry Bulb Temperature HOBO U12-012
lndoor Humidity HOBO U12-012
lndoor Air Velocity Sonic Anemometer
I ndoor Surface Temperatu res Type T Thermocouple and lR camera
Outdoor Weather Conditions DarkSky API
Solar Conditions University of Oregon SRML
1. ConnroRT METRTc DnrnColucreo
E -;905
-
' f*r
ffts*.J'!
\
.-----
L.
2.
3.
4.
5.
5.
lntegrated Design Lab I Boise 10
Managing for Efficiency Based on Operative Temperatures (Report 1708-01)
Office A 20,000 Fr2 RADIANT/WAHP
Office B 83,000 rr2 VAVs?
Office C 4,800 FT2 PAcKAGED RTU
Office D 140,000 rr2 VAV Purur
Office E met 10,600 rr2 PRcrReEo RTU?
Office F e 300 rr2 Ducruss Mltrll-spttr
Figure 1.1 The six sites thatwere chosen foranalysis and the HVAC system ateach site.
With data from logger deployment, the research team was able to calculate thermal comfort
conditions without the need for occupant surveys. The comfort calculation is listed in ASHRAE Standard
55 and is provided as a code in BASIC [7]. The comfort calculation includes the indoor conditions listed in
Table 1, as well as view factors to each surface, and the clothing and activity levels of the occupants. The
activity levelwas set at 1.1 Mets which corresponds to someone sitting and typing. The clothing levelwas
set at 0.57 as that was representative of the clothing observed (shoes, sock, underwear, pants and long-
sleeved button downs). The IDL converted these comfort equations into an Excelsheet so that the comfort
index could be calculated for every data point. ln most cases the data was recorded in five minute
intervals.
The comfort metrics can be calculated in two ways: either as a Predictive Mean Vote (PMV) or as
a Percentage of Population Dissatisfied (PPD). The PMV ranges in its values from -3 to +3, where negative
values are associated with being too cold, and positive values corresponding to being too warm. Thermal
comfort is defined as having a PMV between -0.5 and +0.5. This value is directly related to the percent
that are predicted to be uncomfortable in that situation. For example, a PMV of 1 equals a PPD of 25o/o.
The minimum PPD is 5%.
fl ffi
lntegrated Design Lab I Boise 11
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
4.2 Energy Modeling Methods
The team developed simple energy models for the selected sites in the established, DOE software
program, EnergyPlus. Architectural drawings were obtained for each site either through public records or
supplied by the facilities team. This allowed the IDL research team to replicate the geometry in realistic
detail. The EnergyPlus models were informed by the temperature and thermostat data gathered at the
site instead of ideal assumptions. The HVAC modeling was set to ideal air loads, which meant that the
modelwould provide as much heating or cooling as needed atLOOo/o efficiency to meet the setpoint. The
internal loads were set at ASHRAE defaults for medium to large offices and the construction materials
were selected based on the architectural drawings 18] t9l. By using the recordings from the site, the
research team was able to create schedules that followed the recorded setpoints in 15 minute intervals
so the models could match the recorded behavior.
ln order to run the controls based on measured loads and responses, a framework was created
that can support the simulation inputs and process the outputs. lnstead of using a full year of weather,
the simulation time was shortened to two weeks at most, and simply matched the time during which
instruments were installed at each site. This enabled rapid feedback and provided a window into how the
building was performing. The simulation would run different scenarios including keeping the setpoint the
same or adapting the setpoints and operation times to increase efficiency and comfort. The outputs of
the simulation included comfort and energy metrics: the predicted mean vote and the heating and cooling
energy consumption based on an ideal system. The next step of the process was to develop historical
weather files for the energy models to simulate observed conditions.
lntegrated Design Lab I Boise 12
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
4.2.1 Creoting the Weother File
Developing the weather history file involved three specific phases:
1. Collecting a weather history for a specific time and place.
2. Generating solar radiation data.
3. Formatting the information for EnergyPlus.
Weather histories can be accessed in any number of ways. Many use data from the National
Oceanographic and Atmospheric Association (NOAA). At times, the NOAA data can have gaps or errors in
it. This research relied on a third-party weather resource: the DarkSky Application Programing lnterface
(APl) [10]. The Dark Sky Company is a self-funded software startup that specializes in local weather
observations and forecasts. lt uses bots to access a range of weather histories and forecasts, collects
NOAA satellite information and filters it all. The service is used by Microsoft, Yelp, ConEdison, and others.
Users register for an API key that gives them access to 1,000 free queries each day. The data analyst Bob
Rudis built an R-script that leverages this API and uses a j-son wrapper in order to download this data for
a given set of coordinates on command [11]. The research team adapted Rudis'script in order to download
a weather history specific for the study's locations and times in an hourly format. The script then sends
this output to a comma delimited file for further operation.
EnergyPlus models require 35 weather data points to perform a complete simulation. The fields
of interest from the weather history include the timestamp, precipitation intensity, dry bulb temperature,
dewpoint, humidity, atmospheric pressure, wind speed, wind bearing, cloud cover, and visibility. Many of
these values could be directly used in the EPW forthe simulation, with carefulattention to the units used
in the EPW as described in the EnergyPlus Auxiliary Programs guide. However, many solar fields required
by the EPW had to be calculated. Most of these 35 weather aspects have to do with the quality of sunlight
as this has a major impact on daylighting calculations. Very few weather stations provide the level of detail
lntegrated Design Lab I Eoise 13
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
on solar information contained in the EPW. There are several research stations in the Pacific Northwest
that provide some of this historical information, but this detailed solar data was not available from Dark
Sky or even in the NOAA data recorded at the Boise airport. Therefore, research included the development
of this solar information using solar altitude equations and regressions based on the observed cloud cover,
temperature, and humidity.
4.2.2 Generoting Solor lnformation from the dota for other sites
EnergyPlus parses the solar radiation in the weather file into several different fields. These
include, the extraterrestrial horizontal, extraterrestrial direct normal, horizontal infrared sky, global
horizontal, direct normal, and diffuse horizontal radiation. The Department of Energy has determined
typical values for each of these radiation fields for locations across the country. These values can be found
in the Typical Meteorological Year (TMY) file that is standard for many energy simulations. The solar values
in the TMY are derived from the National Solar Radiation Database (NSRDB). While the NSRDB is derived
from observed data, most of it is modeled [12].
"Neorly oll of the solor dota in the originol ond updoted versions of the NSRDB ore modeled. The intent of
the modeled doto is to present hourly solor rodiotion volues thot, in the oggregote, possess stotisticol
properties (e.9., meons, stondord deviotions, ond cumulotive frequency distributions) thot ore os close os
possible to the stotisticol properties of meosured solor doto over the period of o month or yeor. These doto
do not represent eoch specific hourly volue of solor rodiotion to the some or equivolent occurocy os the
long-term stotistics."
The data that the NRSDB models are based on comes from about 40 stations in the United States.
The stations and data for the Pacific Northwest comes from the University of Oregon Solar Radiation
Monitoring Laboratory [13]. The NSRDB models can vary significantly from the historical observations. For
the four months of the TMY in Boise, lD when observed data were available, the measured diffuse
radiation and the modeled diffuse radiation had a correlation coefficient of only 0.67. This is in stark
lntegrated Design Lab I Boise 14
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
contrast to the observed dry bulb temperatures at the same site which had a correlation coefficient of
0.98 for the same period. The histories must rely on some models to estimate solar radiation based on
sky and temperature conditions. ln order to test the effectiveness of the correlations used for developing
weather data, the team compared the models to observed data rather than the TMY. This is to avoid
comparing a modelto a model, and instead only compares the modelto observed conditions.
The extraterrestrial horizontal radiation and extraterrestrial direct normal radiation in (Wh/m'?)
are a function of the latitude and solar hour. These can be derived using clear-sky solar insolation
equations. The extraterrestrial solar radiation is listed as I, and is the total solar radiation that falts on a
spot above the atmosphere. lt is based on the eccentricity of the earth's orbit around the sun.
lo=lJ$J*f,o
Eo = 1.0001L + 0.034221 cos I' + 0.00128 sin I' * 0.000719 cos 2f + 0.000077 sin 2f
n-7f :2na*
lo = Extraterrestrial direct normal radiation (Wh/m2)
Eo = The Eccentricity of the earth's orbit at a particular time
E = The day angle
n = The numerical day of the year
The Horizontal lnfrared Radiation lntensity from the Sky measured in (Wh/m2) is dependent on
other weather conditions. For locations where this parameter is not recorded or available (e.g. Lewsiton,
ldaho), Wahon and Clark have developed an estimation method [14] [$]:
Hortzontallp = €oT4 6r"6u16
Hori.zontalrR = The Horizontal lnfrared Radiation lntensity from the sky (Wm')
e= The sky emissivity
lntegrated Design lab I Boise 15
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
o = The Stephan-Boltzman constant 5.6697e-8 (W/m2K4)
Tdrybum - Outdoor dry bulb temperature (K)
/,=(o.rw- 0.r64tn(ry;)0.+o.ozzuN+0.003sN2+0.00028N3)
Tdewpoint= Outdoor dew point temperature (K)
N = Opaque sky cover (in tenths)
The opaque sky cover has a minimum value of 0 and a maximum value of 10. The opaque sky
cover is slightly different than the total sky cover. Typically, only the total sky cover is reported. The
fraction of the cloud cover that reflects the solar radiation is called the opaque sky cover. The opaque sky
cover is always less than the total sky cover. The two values are close, and for Boise, lD have a correlation
of 0.91. For the estimate, the opaque sky cover was assumed to be equal to the total sky cover.
The other two solar fields of consequence include the direct normal radiation and the diffuse
horizontal radiation. These are components of the global horizontal radiation. Since this radiation data is
not contained in the DarkSky history, the global horizontal radiation was generated using the Zhang-Huang
model [16]. This correlation could then be used for sites in the area that did not have historical data.
,n =l,,.sin(f) .{t, * c, ff* r, (ff)' + q.(rdbn-roon-,) * r-o}- crft*
/o = The extraterrestrialsolar radiation (Wm'z)
/r = Global Horizontal Radiation lntensity (Wm')
E = Sun's altitude (Radians)
CC = Cloud cover in tenths
Tau = Outdoor air dry bulb temperature at the current hour
Tdbn-s = Outdoor air dry-bulb temperature at three hours previous
lntegrated Design Lab I Boise 16
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
0 = The relative humidity (%)
Ct Cz Ct C+ Cs, and k are regression coefficients specific to the location
The estimation was originally developed for locations in China. Therefore, the team developed a
regression specific to the test sites based on historical observations for locatins in ldaho. The observed
global horizontal radiation intensity for all 8,760 hours was plotted against the estimation. Excel solver
was used with an evolutionary engine solver for non-smooth data with bounds on the constants near the
minimum and maximum observations from Zhang et al. The final regression is shown in Figure 1.2.
Correlation of Global Horizontal Radiation lntensity vs
Estimate for a site in ldaho
1000
900
E 800
a 7ooc.9.E 600
Eg soo
E 4oo
,9 3oo(o
E'i, 2ooU
100
aa
aa'. to..ti.'
aaO3
o R' = o.9r7r
0
0 200 400 600 800
Observed Solar Radiation (W/m2)
1000 1200
Figure 1.2 Results of correlation between horizontal radiation intensity estimate vs observed data for a site in
ldaho based on Tf,lY3 file.
The final correlation showed a correlation coefficient of 0.92 and a Root Mean Squared Error
(RMSE) of 78. This falls within the correlations developed by the Zhang-Huang model.
o a,a
o
a
a
o I
tr
,t'
1
I
bl \
)4 I-lr.
lntegrated Design Lab I Boise 17
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
Table 1.1: Resulting riegression coelficients for Boise, lD from Zhang-Huang model correlation
Co 0.67L205
Ct o.o4L25
Cz -0.32346
Cg 0.004766
Cq -0.0063
Cs 27
k 0.9L427
The global horizontal radiation is further broken down for EnergyPlus into its two components:
the direct normal and diffuse horizontal radiation. There are many models available forthe decomposition
of the global horizontal radiation. The model that showed the best correlation with the recorded data for
diffuse horizontal radiation in Boise was the Watanabe model [17]. This is the same model used by Kwak
et al. [18]. With the diffuse horizontal and global horizontal known, the Perez model can be used to
determine the last remaining solar component [19].
Globallorirontalradiation = Direct6rizontalradiatio"* Dif fus€horizontalradiation
D ir e ct nor or radiation - D tr e ct nori?o?t:! r aaiation
sin(E)
Where B is the solar altitude.
4.2.3 Formatting the Weather Histories
Once downloaded and derived, the weather history data must be manipulated to fit the file
format EnergyPlus models use. EnergyPlus models require a custom file format for weather inputs called
an EPW file or (EnergyPlus Weather file). The first seven lines of the EPW contain generic information
regarding the location and ground temperatures. After this, each line consists of 35 data points of weather
lntegrated Design Lab I Boise 18
Managing for Efficiency Based on Operative Temperatures (Report 1708-01)
information for one hour. The weather data must be formatted in a very specific manner for it to be
compatible with the energy simulation. The run period field in EnergyPlus must be adapted to fit the time-
frame of interest. This run period includes the starting and ending month and day for the simulation as
wellas the name of the weekday on which the simulation is to begin.
While the simulation can be started and stopped for any day, it must start and end at midnight.
The EnergyPlus simulation cannot be started at any random hour. As a consequence, the weather data
file must have a range of inputs equal to or longer than the run period. For example, if the energy model
requests a simulation from Ll25 to 1/27, the EPW must have data for at least tl25 O:OO - Ll27 24:OO.ll
the weather observation is from L/25 O7:OO - Ll27 07:00, extra data must be added to the file for the
hours of Ll25 O:OO - tl25 07:00 and from Ll27 07:00 - 24:OO. This can be done by either repeating data
lines, or stitching together weather history and projections to extend the weather file to the full time
required. ln this research, the weather histories were appended to older observed weather conditions to
create full data sets for the simulations. The simulation outputs were then filtered for the outputs during
the hours of interest. ln order to produce this weather data set, the R-script from Rudis was adapted to
have a starting and ending date with a for loop that sends an API request for each 24-hour period during
that timeframe, appends all of the data, and downloads it to a comma delimited file. The researchers
developed an Excel workbook to automatically parse the observed data into the EPW order and derive
the solar fields based on the equations listed above. The Excel book uses macros to automatically export
a comma delimited file in the format of the EPW. Once the file extension is changed it can be used with
any EnergyPlus or OpenStudio model.
5. Monronme Rrsulrs
lntegrated Design Lab I Boise 19
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
The research team collected data at each of the sites during both heating and cooling seasons. The
recordings were taken at each relevant surface so that the mean radiant temperature could be calculated.
The surface temperatures were relatively tightly grouped within a few degrees of each other, except for
the windows which showed very strong deviations from the rest of the surfaces.
SURFACE TEMPERATURES OFFICE D JUNE 2018
90"F
85"F
80'F
75"F
70"F
65'F
6/22 6122 5/23 6/23
0:00 t2:00 0:00 12:00
-l}t-122
(window)
slDt-541 (floor)
6/24 6/24 6/2s 6/2s 6126 6/26
0:00 12:00 0:00 12:00 0:00 72:00
-
tDL-127 (W.Wall)
-
rDL-s6s (ceiling)
IDL-564 (central desk)
-lDP-005
(E.Wall)
6127 6127 6128 6/28
0:00 L2:00 0;00 12:00
-
IDL-123 (N.wall)
-
IDL-130 (S.Wall) ERROR
Figure 1.3: Recorded surface temperatures at Office D
All offices had a PMV below 0, indicating a trend towards being too cool for occupants in office-wear
who are sitting and typing. Even during the fall, when the outdoor air temperature rose above the balance
point of the building, most offices showed a tendency to stay cold. One instance of this was at Office C
during October and is displayed in Figure 1.4.
lntegrated Design Lab I Boise 20
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
OFFICE C PMV October 20L7
8070
6050r
i85
20
10
0
o-
0
-0.5
-1
-1.5
-2
-2.5
-3
\..
o" *r f +* +* +r f *1 € +1 +t+t f +1 f *1 f +t +1 +1 f*oN '
Figure 1.4: The comfort index (PMV) measured at an open office in October
Most measurements occurred over an extended time period. ln order to identifo daily trends in
the comfort, the team layered the daily calculations on top of one another as shown for a different site in
Figure 1.5.
OFFICE D PMV OCTOBER 2017
0
12:00 AM 3:00 AM 6:00 AM 9:00 AM 12:00 PM 3:00 PM 6:00 PM 9:00 PM 12:00 AM
-0.5
1.5
T
0.5
1
1.5
*Mon - 9 *Tue - 10 .-Wed - 11 -Thu - 12
Figure 1.5: The comfort index measured at a site with the weekday information layered in different colors
Layering the weekdays showed a general profile of chilly conditions in the mornings with
increasing comfort in the afternoon. Many offices showed trends well below the comfort standard of -
TOOWARM
lntegrated Design Lab I Boise 2l
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
0.5. For example, many weekday readings at Office B dropped down below a PMV of -1 as shown in Figure
1.6.
Office B cubicle winter PMV - weekdays
0
-0.5
-1
-1.5
-2
12:00 AM 3:00 AM 6:00 AM 9:00 AM 12:00 PM 3:00 PM 6:00 PM 9:00 PM 12:00 AM
+Fri - 10 4-Mon - 13 -**Tue - 14 Wed - 15+Thu - L6
+tri- t7 +Mon-20+Tue-21 -{-Wed-22+Thu -23
-+Fri-24 Mon - 27+Tue - 28 -+Wed - 29
Figure 1.6: Comfort measurements recorded in November 2017 at Office B
The trend of offices to be too cold continued even into the summer data collection period as
shown in Figure 1.7.
Office D PMV June 2018
-0.5
-2
12:00 AM 3:00 AM 6:00 AM 9:00 AM 12:00 PM 3:00 PM 6:00 PM 9:00 PM 12:00 AM
-+Fri -22 +Sat-23 +Sun -24 -+- Mon-25 +-Tue-26 Wed-27 +Thu-28
0
7
1.5
Figure 1.7: The Predicted Mean Vote calculated based on measurements taken at Office D
lntegrated Design Lab I Boise 22
Managing for Efficiency Based on Operative Temperatures (Report 1708_0U
To present the data of Figure 1.7 in an alternative way, the same comfort information is listed in
Figure 1.8 as a calculation of the percentage of people that are predicted to be dissatisfied with the
thermal conditions in the office.
PERCENTAGE OF PEOPLE DISSATISFIED Office D 2018
60%
50%
40%
3A%
20%
70%
o%
12:00 AM 3:00 AM 6:00 AM 9:00 AM 12:00 PM 3:00 PM 6:00 PM 9:00 PM 12:00 AM
--{-Fri -22 --.}-Sat-23 -*'-Sun -24 + Mon -25 ."-*^Iue-26 Wed-27 -.-+-Thu -28
Figure 1.8: The calculated prediction of the PPD atOffice D in June 2018
While the comfort index is trivial during the unoccupied hours of the building the discomfort was
actually shown to trend higher during the occupied hours of the building from 8:00 AM - 5:00 PM. This
same trend could be seen at Office B in July. The shark-fin curves displayed in Figure 1.9 show how at
night, the temperature rises in the open office, bringing it closer to the desired PMV of O but as soon as
cooling starts again in the morning, it becomes uncomfortably cold.
lntegrated Design Lab I Boise 23
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
Office B July PMV
0
-0.5
-1
-1.5
-2
^f
Figure 1.9: Measured comfort at Office B in July
5.1 Thermostat Reading Versus Other lnstruments
One of the unanticipated results was that the average air temperatures recorded in the offices
deviated from the air temperatures recorded at the actual thermostat location. The ADA required
mounting height for a thermostat is between 48 and 54 inches. However the center of mass for the seated
height of most individuals in an office is significantly lower (between 23 and 25 inches) and is the height
at which most air temperature recordings were taken (excluding the floor and ceiling measurements). ln
each case, the recording taken adjacent to the thermostat was higher than the average office air
temperature by at least 0.5oF, and sometimes as much as 2oF. The recordings at three different sites are
shown below in Figure 1.10, Figure 1.11, and Figure 1.12.
lntegrated Design Lab I Boise 24
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
AIR TEMPERATURES AT OFFICE D JUNE 2018
75"F
74"F
71"F
?2"F
rI
7L"F
70"F
6122 6122 6123 6123 6/24 6/24 6/2s 6/25 6126 6/26
12:00
6/27 61270:00 12:00
6/28 6/28
0:00 12:O00:@ 12:00 0:00 12:00 0:0O 12:00 0:00 12:0O 0:00
-Thermostat -Average
Figure I .10: Recorded average air temperature verrus recorded temperature next to thermostat at Office D
AIR TEMPERATURES AT OFFICE B JUNE 2018
80
79
78
77
76
75
74
73
72
7llL 7h3 Tlrs 7/L7 7lt9 7/2t
-MEDIAN Air Temp -Thermostat Temp
7 /23 7/2s 7 /27
Figure 1.1 1 : Recorded average air temperature versus recorded temperature next to thermostat at Office B
82"F
80"F
78'F
76'F
74'F
lntegrated Design Lab I Boise 25
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
AIR TEMPERATURES AT OFFICE F JUNE 2018
72'F
6/13/2018 0:0o 6114/20taotco 6/15/2018 0:00 slrglzolao:oo 5/Ltl2oraotoo 6/18/20180:00 6119120180:00 6/20/20180:00 6l2tl2o1ao:OO 6l22l2otao:@
-Average -Above-Tstat
Figure 1 .12: Recorded aveEge air temperature venius recorded temperatuie next to thermostat at the
lntegrated Design Laboratory
5.2 Energy Modeling Results - Winter
Based on the recorded weather and setpoints, the energy models were able to re-create the
historical observations. Once verified, the research team used the energy models of the case study
buildings to test alternative control strategies. This allowed the team to essentially go back in time and
see what the effects of adjusting the HVAC operation would be by providing the models the same weather
patterns, but supply different control signals. The control strategies were developed directly in
EnergyPlus. The control strategies were simple in nature - similar to an air-based thermostat, but with a
weighting factor for the surface temperatures to better manage thermal comfort and energy savings.
While it was possible to save both energy and increase comfort by eliminating over-cooling during the
summertime, this was not the case during the winter. The office conditions indicated chilly occupants and
increasing the heating setpoint would increase energy consumption. The IDL research team looked at
changing occupant behavior by increasing the simulated clothing level to 1.0. This was effectively
lntegrated Design Lab I Boise 26
Managing for Efficiency Based on Operative Temperatures (Report L7A8_0L!
modeling everyone wearing a sweater at work. The baseline comfort based on standard office wear at
this site is shown in Figure 1.13.
OFFICE E Modeled Comfort at CLO = 0.57
0
-0.5 .*15-Jan
*16-Jan
*17-Jan
*18-Jan
*19-Jan
*22-Jan
-1
-1.5
o-
-2
891011
891011
L2 13
HOUR
74 15 16 t7
t4 15 15 17
Figure 1.13: Modeled comfort at Office E during observation based on typical office wear (trousers and long
sleeves)
The modeled comfort at the Lewsiton office showed very cold conditions with conditions well
belowtheASHRAE minimum of -0.5whenoccupantswere modeled aswearingconventionalofficeoutfits.
The effect of increasing the clothing level is shown in Figure 1.14.
OFFICE E Modeled Comfort at CLO = 1.0
0
1
2
o-
-0.5
-1.5
*15-Jan
*15-Jan
*17-Jan
-18-Jan
-l-9-Jan
*22-Jan12 13
HOUR
Figure 1.14: Modeled comfort at office E during ohservation based on increased clothing levels (adding
sweaters)
lncreasing the clothing level brought the modeled PMV closer to the ASHRAE minimum of -0.5,
but many hours still dipped below this range. Therefore, within the energy model the setpoints were
lntegrated Design Lab I Boise 27
Managing for Efficiency Based on Operative Temperatures {Report 1708_01}
adjusted from what was observed and increased to 72'F while maintining a clothing level of 1.0 (wearing
sweaters). The results are shown in Figure 1.15.
OFFICE E MODELED HEATING SETPOINT 72oF, CLO =1.0
0
-0.5
*1.5
-1.6*L7
-L8*L9
*22
*23
*24
-1.
8 9 10 LL 12Horr13 t4 15 L6 t7
Figure 1.'15: The modeled comfort at Office E based on increased clothing level and an increased heating
setpoint of 72oF
lncreasing the heating setpoint did increase the modeled heating load, but managed to bring the
predicted comfort metric within ASHRAE's acceptable PMV range of -0.5 to + 0.5.
5.3 Energy Modeling Results - Summer
With an emphasis on saving energy while providing comfort, the cooling setpoints were increased
until the PMV during the occupied hours was closer to 0. ln general, the ideal cooling setpoint to provide
a minimum PMV was 76oF. Setback were increased to 80oF to account for the surface temperatures and
comfort calculations. lncreasing these setpoints improved predicted comfort and significantly reduced the
cooling load. The results of this altered control are shown in Figure 1.16.
o_
-1.5
2
1.00
0.50
0.00
-0.50
(U
o
c(o
OJ
-o
0)
.UE
OJ
o-
lntegrated Design Lab I Boise 28
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
OFFICE A PMV FOR JULY 10-14
*As-ls Operation
Model
+tvtodeled (by
OpenStudio)
-1.00
^f
^"* ^Ie9,)o 9ao
,t^r,CJ^"C^orto**^,**roor*+*^rosro+uoer
-$S -$S nY (os $d $, (s$ (so t(' (\' C
Figure {.16: The resulting comfort from increasing setpoints (black} versus observed controls (blue) atthe
Office A
For Office E i, the current operation showed operation in a comfortable range, but with a still slightly
negative PMV. lncreasing the setpoint slightly up to 75"F was still able to save energy and keep the comfort
index closer to the ideal value of 0 as shown in Figure 1.17.
Office E Thermal Comfort August 2018
L
0.5
0 J.a?aaaOof
J-ffJr-.rE
tA
-0.5
-1
812 813 814 8/s 8/6 817 818 8ls 8/10
o Baseline o Proposed
Figure 1.17: Predicted comfortmodeled with proposed (black) setpoints versus observed setpoints (blue)
The energy impacts of increasing the setpoint vary based on the HVAC type and efficiency at each
site. ln order to provide uniform comparisons, the models only estimated the amount of cooling load that
was reduced during the observed week. Actual energy savings from these loads may be up to four or five
?,l)p
atl-,a,
a&,
lntegrated Design Lab I Boise 29
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
times lower depending on the EER of the cooling equipment and its part-load performance. However, the
models were able to quantify the kBtU of total cooling load that could be reduced by using the new
setpoints and setbacks and the percent reduction in load over the observed week that was simulated. The
results are shown for each site in Figure 1.18.
OFFICE A 39%
L5%
48%
32%
sL%
OFFICE B
OFFICE C
OFFICE D
Figure 1.18: Cooling load reduction predicted for each site based on increasing cooling setpoint to 76oF to
better meet comfort metrics.
The simulation results were used to estimate energy savings and comfort impacts of incorporating
surface temperatures into thermostat controls. The research identified the savings possible by shifting
controls from their current baseline settings to a strategy that is more in line with the demands of
occupant comfort. Based on the research findings, the development of the alternative controls could
prove useful and marketable to controls engineers, consultants, and building operators.
One of the key findings from this project was that when one considered all aspects of comfort
(including surface temperatures) allthe offices studied were found to be uncomfortably chilly even during
the summer. ASHRAE mandates a minimum PMV of no lower than -0.5, but offices were found to be
regularly dipping below this and over-cooling the spaces. This finding was borne out anecdotally through
1
2
3
4
5 OFFICE E
r&
(450 KBru/wK)
(5,650 KBru/wK)
(550 KBru/wK)
(1,200 KBru/wK)
(1,150 KBru/wK)
6. DrscussroN AND FuruRr Wonx
--rr
lntegrated Design Lab I Boise 30
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
multiple comments from the occupants and from the many electric space heaters that were observed
under employee desks.
ln every situation measured, the air temperature recorded next to the thermostat was higher
than either the average or the median office air temperature measured closer to the office worker's
location. This meant that employees were experiencing setpoints that werel-2oF colder than the
thermostat's setpoint. This could be due to the height disparity between a seated worker's center of mass
and a thermostat's installed height. lt may also be due to the warmth generated by the electrical current
running to the thermostat. The largest temperature disparities were found for "smart" thermostats with
colored graphics and more controls which have a higher power draw. More careful experimentation
would be needed to quantify the exact nature of this relationship, however the research did uncover
enough of a disparity that this could be one of the contributing factors to overcooling in offices.
The simulations showed that for most sites the chilly conditions could not be fully overcome by
changing occupant behavior (encouraging sweaters). lnstead, most sites also required an increase in their
heating setpoints up to 72"F with the increased clothing level in order to meet the ASHRAE 55 comfort
standards. The research team did observe that the comfort increased in the offices throughout the day as
the surface temperatures in the space slowly rose from internal gains. Even in the winter, there may be
some financial gain to increasing the setpoints. For example, increasing the setpoints at Office E increased
the heating load by approximately 2oo/o per week. For a small office of this size (10,000 ft2) this translates
to between 150 - 300 extra therms of gas per year. Even assuming an extra 300 therms of gas is required
each year to raise the setpoints, this may offset the use of many space heaters present in individual offices.
Purchasing these extra therms may cost the customer at most an extra S:OO per year, but with over a
dozen employees in the office and Berkeley's finding of a SSEO productivity benefit per employee when
comfort conditions are satisfied, this increase in gas consumption should have a net financial benefit in
employee output.
lntegrated Design Lab I Boise 31
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
lncreasing the cooling setpoint during the summer provides an even stronger financial incentive.
lncreasing the cooling setpoint to 76"F could bring more office areas into compliance with ASHRAE's
comfort standards. ln addition, simulation results showed savings of 15 - 40% of the cooling load.
Assuming a generous EER of L7 for this cooling equipment, that would still result in at least 3 -8%of
cooling energy saved at each of these sites during each of the week studied.
The incentive for this study was based on the effect surface temperatures have on comfort. The
research team found that by incorporating the surface temperatures to develop holistic comfort metrics,
the air temperature thermostat setpoints could be changed to increase the comfort of office employees
in the Pacific Northwest. This simple change resulted in significant savings and other studies suggest that
it would also increase employee happiness, wellbeing, and productivity. At the very least, engineers,
controls manufacturers, and building managers should re-visit the default heating and cooling setpoints
of 7O -74"F that are currently in place in most offices.
Operative controls could rely on severalthermocouples as in this study which are inexpensive and
widely available sensors that can be easily integrated into a control sequence. Alternatively, infrared
cameras could also be used to map surface temperatures and provide better comfort metrics. As the
operative temperature control approach is adopted, the technology allows either building managers or
utility companies to provide incentives for this type of control if savings are verified. A simple control
scheme using operative temperatures will encourage efficient control setpoints that endure. The market
path may include the adoption of this control strategy by a controls company or as a new tool used by
consultants and building operators.
lntegrated Design Lab I Boise 32
Managing for Efficiency Eased on Operative Temperatures (Report 1708_01)
These hours reflect only Avista's contribution to this project and are not reflective of total project
investment by the research team, industry sponsors, or other university staff.
FY77'-Y78
Salaries
Fringe:
Travel:
F&A:
Tuition
S11,G84
S1,052
S1,ooo
56,91o
s3,355
Total:524,oLI
lndirect Costs
For this contract, Ul-lDL was considered an on-campus unit of the University of ldaho with a federally
negotiated rate of 50.3%.
7. Buoeer SurunnnRv
Personnel Hours estimate Description
Elizabeth Cooper 50 Provide overallmanagement of the project
Damon Woods, P.E.120 Provide technical support and execute daily
tasks ofthis project
Neha Pokhrel 200 Energy modeling and reporting
Ryker Belnap 200 Energy modeling and data processing
lntegrated Design Lab I Boise 33
Managing for Efficienry Based on Operative Temperatures (Report 1708_01)
8. RrreRrrucrs
t1l E. Arens, M. Humphreys and H. Zhang, "Are 'Class A' temperature requirements realistic or
desirable?," Building ond Environment, vol.45, no. L, pp. 4-10,2010.
l2l B. Olesen, "Operative temperature control of radiant surface heating and cooling systems," in
Clima 2007 WellBeing lndoors, Helsinki, 2007.
t3l N. Fernandez, "Energy savings modeling of standard commercial building re-tuning measures:
large office buildings," Pacific Northwest National Lab Report 2L596, Richland, WA,2072.
t4] ElA, "Commercial Building Energy Consumption Survey - E1. Major fuel consumption by end use,"
U.S. Energy lnformation Administration, Washington, D.C., 2012.
t5l T. Hoyt, E. Arens and H. Zhang, "Extending air temperature setpoints: Simulated energy savings
and design considerations for new and retrofit buildings," Building and Environment,2OL4.
t5l S. Tom, "Managing Energy and Comfort," ASHRAE, no. 6, pp. 18-26, 2008.
I7l ASHRAE, "ASHRAE, ANSI/ASHRAE Standard 55-2013. Thermal Environmental Conditions for Human
Occupancy," American Society of Heating Refrigerating, and Air-Conditioning Engineers, lnc.,
Atlanta, 2013.
t8l ASHRAE, Handbook of Fundamentals, Atlanta: ASHRAE, 201-7
t9] ASHRAE, "ASHRAE Guideline 14 - Measurement of Energy and Demand and Water Savings,"
American Society of Heating and Refrigerating Engineers, Atlanta, 2002.
[10] Dark Sky Company LLC, "Dark Sky APl," June 2012. [Online]. Available: https://darksky.net.
[Accessed 15 January 20L71.
[1-L] B. Rudis, "R interface to the Dark Sky APl," GitHub, 22 September 2016. [Online]. Available:
https ://githu b.com/h rbrmstr/da rksky. [Accessed 15 Jan ua ry 2OL7l.
[12] S. Wilcox, "National Solar Radiation Database 1991-2010 Update: Users Manual," National
Renewable Energy Laboratory, Golden, Colorado, 2012.
[13] University of Oregon, "University of Oregon Solar Radiation Monitoring Laboratory," t2 July 20L3.
[On line]. Ava ila ble: http://solardat. uoregon.edu.
lntegrated Design Lab I Boise 34
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
[14] G. N. Walton, "ThermalAnalysis Research Program Reference Manual," National Bureau of
Standards, 1983.
[15] G. Clark and C. Allen, "The Estimation fo Atmospheric Radiation for Clear and Cloudy Skies," in
Notionol Possive Solor Conference, 1978.
[16] Q. Zhang, J, Huang, Y. Hongxing and L. Chengzhi, "Development of Models to Estimate Solar
Radiation for Chinese Locations," Journal of Asian Architecture and Building Engineering, vol.41,
2003.
[17] T. Watanabe and e. al., "Procedures for separating direct and diffuse insolation on a horizontal
surface and prediction of insolation on tilted surfaces," Tronsoctions, Architecturol lnstitute of
Jopon, no. 330, 1983.
[18] Y. Kwak, D. Seo, C. Jang and J.-H. Huh, "Feasibility study on a novel methodology for short-term
real-time energy demand prediction using weather forecasting data," Energy and Buildingg vol.
57, pp.250-260,20L3.
[19] R. Perez, R. Stewart, R. Seals and TedGuertin, "The Development and Verification of the Perez
Diffuse Radiation Model," Albany, NY, 1988.
[20] T. Nouidui, "bcvtb forum," 29 May 2015. [Online]. Available
htt ps ://g ro u ps. go og I e. co m/fo ru m/# I f o ru m/ bcvt b.
[21] S. Karg, "SourceForge," 15 October 2013. [Online]. Available: http://bacnet.sourceforge.net/.
l22lY.-J. Wen, "Rapid-Prototyping Control lmplementation using the Building Controls VirtualTest
Bed," Philips, Briarcliff Manor, 2011.
t23] X. Pang, M. Wetter, P. Bhattacharya and P. Haves, "A Framework for Simulation-Based Real-Time
Whole Building Performance Assessment," Building ond Environment, pp. tOO-108,20t2.
[24] M. Wetter, "Co-simulation of building energy and control systems with the Building Controls
Virtual Test Bed," Journol of Building Performonce Simulotion, pp. 185-203, 2011.
[25] T. Nouidui, M. Wetter, Z. Li,X. Pang, P. Bhattacharya and P. Haves, "BacNet and Analog/Digital
lnterfaces of the Building Controls Virtual Testbed," in Conference of lnternotionol Building
Performonce Simulation Associotion,Sydney, 2011.
[25] ASHRAE, "ANSI/ASHRAE Standard 62.1.-2007 Ventilation for Acceptable lndoor Air Quality,"
American Sociaety of Heating, Refrigerating and Air-Conditioning Engineers, lnc., Atlanta, 2007
lntegrated Design Lab I Boise 35
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
[27] ASHRAE, "ASHRAE Guideline 0-2005: "The Commissioning Process"," American Society of Heating,
Refrigerating, and Air-Conditioning Engineers, Atlanta, 2005.
[28] P. Haves and P. Xu, "The Building Controls Virtual Test Bed - A Simulation Environment for
Developing and Testing Control Algorithms Strategies and Systems," in lnternotional Building
Performo nce Simulotion Association, Beijing, 2007.
[29] E. Mills, "Building Commissioning: A Golden Opportunity for Reducing Energy Costs and
Greenhouse Gas Emissions," Lawrence Berkeley National Lboratory, 2009.
[30] K. Roth, D. Wesphalen, J. Dieckmann, S. Hamilton and W. Goetzler, "Energy Consumption
Characteristics of Commercial Building HVAC Systems Volume lll: Energy Savings Potential,"
Department of Energy, Cambridge, 2002.
[31] D. Westphalen and S. Koszalinski, "Energy Consumption Characteristics of Commercial Building
HVAC Systems Volume ll: Thermal Distribution, Auxiliary Equipment, and Ventilation," U.S.
Department of Energy, Cambridge, 1999.
[32] D. Baylon, D. Robison and M. Kennedy, "Baseline Energy Use lndex of the 2002-2004
Nonresidential sector: lD, MT, OR, and WA," Northwest Energy Efficienry Alliance, Portland, 2008.
t33] S. A. M. Maleki, H, Hizam and C. Gomes, "Estimation of Hourly, Dai[ and Monthly Global Solar
Radiation on lnclined Surfaces: Models Re-Visited," Energies, vol.10, no.\34,2017.
lntegrated Design Lab I Boise 36
Managing for Efficiency Based on Operative Temperatures (Report 1708_01)
Location Start Date Start Time End date End Time
Office F elzeltT 12:00 pm 70l6lL7 9:00 am
Office A 4lLsl77 12:00 pm sl77177 8:30 am
Office C 70lt3lL7 12:00 pm 7O123177 12:50 pm
Office B LulolLT 12:00 pm 7t120177 - office
ttl29lL7 - cubicle
L0:00 am
10:00 am
Office D LOlsl2OtT 12:00 pm 10/L2/77 12:00 pm
Office E 7lL2lL8 2:00 pm 1./2s/L8 10:00 am
Location Start Date Start Time End date End Time
Office A 1/e117 8:00 am 7 /]-s/L7 12:00 pm
Office C 6lslt8 2:00 pm 6lLsl78 12:00 pm
Office B 1/13/L8 12:00 pm 7124118 12:00 pm
Office D 6l22lL8 12:00 am 5lzel78 12:00 am
12:00 pmOffice E 8/1.178 12:00 pm 8le/t8
9. Appruorx
2. Wrrren DaraCouecrox Dares
il. SunnrvrER DArA Courcrroru Derrs -l
APPENDIX H
Final Report: Robust Microgrid
*lnsta #
Universityotldaho TfrCollege of Engineering
A Reactive Future
Project Duration: 10 months Project Cost: Total Funding $83,712.89
OBJECTIVE
Create a sustainable planning process toprovide non-wire alternatives to integrated
capacity planning by a four-objective design
process:
1. Determine the state of similar technology in
comparable situations. Assemble, analyze,
and explain their Distribution Resource Plans
(DRP) in the context of Avista@'s situation.Integrate renewable resources, peaking
capabi lities, and applicable standards.
2. Develop a planning capacity in the context
of Avista@'s incumbent DRP. Include methodsfor integration capacity analysis (ICA) and
locational net benefits analysis (LNBA).
Determine how many distributed energy
resources (DER) the system can handle and
how to calculate the value of those DER.
3. Apply the planning methods to operational
scenarios such as a case provided by Avista.
Derive appropriate planning studies to
determine hosting capability, locational
marginal price, and system capacity. Lay out
operational guidelines to determine which DER
should be added, when to add them, and howto equip them with smart invefters for
interface in operational scenarios.
4. Create energy and capacity products and
services that can be packaged and marketed
from what is learned. Use open source
applications such as GridlAB-D. Attract follow-
on funding.
BUSINESS VALUE
The software products created in this project,
when refined for manufacture, may be
packaged, and sold. While planning software
may be sold, the underlying open source
applications are available at little or no cost.
This open source concept makes the software
products economically attractive.
INDUSTRY NEED
As accomplished under objective #1, we find
that there is an industry need for such planning
software at a competitive price. There is valuein providing such plug-and-play software,
value that companies, including utilities, are
willing to pay for. The open source nature of
the software presents the opportunity for
individual users to not only suggest ideas on
what might change within the software but to
tailor the software as desired.
BAGKGROUND
The relationship between the electric utility
and its customers is changing. Utilities are
becoming less retailers of a commodity and
more brokers of energy resources. The advent
of competitive DER provides opportunities to
broker a wide range of energy resources.
Managing these resources to provide stableand reliable service requires verified
simulations of the systems for power
distribution. These simulations and analyses
are impoftant for utilities to predict and solve
problems that arise in providing reliable power
to customers. Simulation software proprietaryto private businesses require licenses that
often are expensive. An open source solutionis currently an opportunity in the power
distribution simulation and analysis field.
SCOPE
Task 1: Location Value Analysis
The initial task is to describe the location and
the subsequent standing of the hardware
within the vicinity. Given the developing
housing infrastructures and their increasing
demand as a load as well as customer
preferences, there in an opportunity to include
sufticient DER in the solution.
Investigation took place which noted that
locations like California have considered waysin which to integrate technology upgrades
which do not require new and extensivehardware enhancements. Smaft-Grid
improvements can be accommodated into the
system allowing for reduced cost while still
maintaining the system. A one-model format is
necessary.
Task 2: Distributed Resource Plans
This task is to develop alternative solutions
using DER to satisfy increasing demand.
Smart applications should improve the status
quo while also accounting for the growing
demands of the system.
Design alternatives are proposed.
Comparisons analyze feasibility in the contextof close proximity to residential locations.
Simulation of appropriate models suppofts and
demonstrates the effectiveness of alternatives.
Task 3: Non-Wire Solutions
For this task, Gridl-AB-D was chosen as the
open source platform. Simulations in a script-
based language provide a means of analyzing
non-wire solutions. A few supplementary
applications greatly aid in visualizing the
results.
Gridl-AB-D requires support from software
such as Blazegraph and Ubuntu to overcome
issues of file conversion or translation from the
CIM models. We found a need for a more
streamlined, transparent means to adapt
existing Avista@ data for analysis within
Gridl-AB-D. For example, data for the
overhead lines must be manually converted to
some degree from CIM models to Gridl-AB-D
data files. Significant amounts of time werespent organizing and performing this
conversion process. This problem defined the
endpoint of the project's work. We did
describe the issue to document the file
conversion issue.
Given the extent to which appropriate open
source applications are employed, we createda user manual to explain the current
understanding of the software, to give
direction for running simulations, and to
provide understanding for future teams to
improve operations.
Task 4: Final Repod
This Final Repoft summarizes the results from
the project, including models, the proposed
solutions, and recommendations.
DELIVERABLES
The deliverable for this project is a User
Manual of the GridlAB-D based software andother relevant applications, installations,
operations, and graphic demonstrations
PROJECT TEAM
PRINCIPAL INVESTIGATORS
Name Dr. Herbert Hess
Orqanization University of Idaho
Contact #[phone]
Email [e-mail]
Name Dr. Brian Johnson
Oroa n ization University of Idaho
Contact #[phone]
Email bjohnson@ uidaho. ed u
Name Dr. Yacine Chakhchoukh
Oroanization [Jniversitv of Idaho
Contact #(208) 885- 1550
Email vacinec(A uidaho.ed u
RESEARCH ASSISTANTS
Name Jacob Dolan
Oroanization University of Idaho
Email dola9260@vandals. uidaho.edu
Name Nick Flynn
Oroanization Universitv of Idaho
Email flvn 1026@vandals. uidaho.edu
Name Barias Alruwaili
Oroanization University of Idaho
Email alru4168@vandals, uidaho.edu
Name Tianvi Chen
Oroanization l,niversiw of Idaho
Email chen I 285@vandals. uidaho.edu
Name Maximilian Schnitker
Oroanization Universiw of Idaho
Email schn6884(avandals. uidaho
Name Daniel Allen
Orqanization Universiw of Idaho
Email alle82 13@vandals. uidaho.edu
Name Jesse Stranqe
Oroanization Universiw of Idaho
Email stra6884@vandal s. uidaho.ed u
TASK TtTE
ALLOCATED
START
DATE
FINISH
DATE
Location Value Analysis 5 months Sep'17 Feb'18
Distributed Resource
Pla ns 3 months Feb'18 May'18
Non-Wire Solutions 2 Months Early
May'18
Early
Jul'18
Final Report 2 weeks Early
I ul'18
Mid
lul'18
SCHEDULE
EXECUTIVE SUMMARY
Grid analysis is growing to not only
accommodate current demands but also be
designed with future planning as a large
portion of its capability. Acquiring the capable
software can quickly become a costly venture
that results in alternatives being considered.
This project aims to determine the state of
appropriate technology of peer companies, to
develop a planning capacity within the context
of Avista@'s incumbent DRP, to apply these
planning methods to operational scenarios,
and to create energy and capacity products
and services to be packaged and marketed.
The project accomplished the first two of these
objectives and addressed an ongoing project
scenarios for explore grid analysis through
open source software which has the potential
to incorporate smart applications while also
conducting analysis on the systems currently
built that have been added within the program.
I. RESEARCH MOTIVATION
The motivation for this research project is to
employ DER more effectively. DER are
coming. They fit well into a transactive model
of energy distribution. Smart grid applications
promise an opportunity for reduced costs and
software flexibility. Energy and capacityproducts and services, packaged and
marketed, provide an economic opportunity.
Due to the nature of the current location being
tested and the advantages of open source
software as a platform, this project is an
opportunity to develop useful products for
growing and adapting distribution systems at a
cost advantage. Avista@'s grid data presents a
great opportunity for thorough testing of
software in a realistic distribution context.
II. PROJEGT BACKGROUND
Transactive electrical distribution is coming.
This project seeks to create software that
incorporates transitive energy distribution into
distribution planning. The development in the
setting area serves as a vehicle to identify
current technology, to develop tools and
methods to include DER into the distribution
model, and to simulate and demonstrate
design improvements using this technology in
a practical setting. Various resources can be
incorporated and tested, for example,
previously collected Synergy data for the
region and hardware profiles and updates.
Correct formatting and translation of data into
compatible formats are necessary for useful,
transparent, and accurate models.
GridLAB-D was chosen for this purposes of this
project as Avista@ is partnered with its
designers, Pacific Northwest National Labs
(PNNL). Open source software was considered
for flexibility and as a cost-saving measure.
Open source software is, on the other hand,
primarily user driven and can be difficult to
maintain if the user base is not large or
suppofted sufficiently.
Along with Gridl-AB-D, there are other open
source applications that help to facilitate the
simulations and analysis including Blazegraph,
GLM Plotter, and Ubuntu. These provide the
missing conversion process and a graphical
user interface that are fundamental in
understandi ng software capabilities.
!II. SPEGIAL TECHNOLOGY UTILI,Z,ED
A CIM to GLM Converter written at PNNL,
Blazegraph, GLM-Plotter, GridLAB-D, and
VirtualBox and were used over the course of
this project.
a. Applications Descriptions
Blazegraph:
Blazegraph is an open-source, large data
analytic application that utilizes queries to sort
through data and return tabulated results.
These tabulated results can then be expofted
as CSV or GLM files. This software must run onit its own command terminal, opened in an
internet browser.
GLM Plotter:
GLM Plotter is an open-source visualization tool
for GLM files that are used in Gridl-AB-D. The
GLM Plotter is best used when flrst learning
Gridl-AB-D as it intuitively displays how the
software is interpreting the code. For larger
systems, GLM Plotter runs slow and tends to
be tedious in its data structure.
GridLAB-D:
Gridl-AB-D is an application that simulates
power distribution systems. The program uses
discrete time steps and data regarding the
power system to run a power-flow analysis.
These simulations can output various kinds of
data depending on the users'preferences.
ViltualBox-Ubuntu:
The operating system Ubuntu is required to run
the CIM2GLM converter. ViftualBox is an open-
source software used to create a virtual spacefor Ubuntu to run alongside a different
operating system. This allows multiple
operating systems to run on one computer.
CIM2GLM Convelter:
The CIM2GLM converter is an application
created by PNNL that takes in CIM document
and converts it into an equivalent GLM file that
can be used by Gridl-AB-D. Performance is
acceptable, but there are problems with how
some of object are converted.
b. Proiect Procedure
The project initially began with considerations
being made that our system would require a
status check. Figure 1. shows the geographical
layout of the system and the accompanying
feeder names. The first task, Location Value
Analysis, identifies the best location of
distributed energy resources through a
Gridl-AB-D al rithm
Figure 1. BLU 321 (Orange) & OGA 611
(Btue)
Preliminary constraints for the project, shown
in Figure 2. demonstrate a possible course of
action for the project. While the feeders from
Figure 1. are currently under construction in
some locations, possible DER solutions were
investigated through simulations.
Table 4: Proied Type! and Potentlal for DER Defernl
td(iron CeEily Yq *ih Erlsilln@ EciffiB
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Figure 2. Possible DER Deferra!
Results of historical investigations as shown in
Figure 2 may be illustrated, for example, as
shown in Figure 3. The data shown for years
prior to 2018 are actual data; those 2018 and
beyond are projections.
f
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Figure 3. Transmission Load Studies and
Seasonal Operational Constraints
The next step is to prepare DER Plans. Figure
4 illustrates such a plan, outlining outlined
how to optimize DER values.
8 @
Figure 4. Optimizing DER Value
Though Gridl-AB-D was the software to
develop and optimize the planning,
PowerWorld@ was selected to visualize the
situation for presentations. This helps
illustrate where the DER could be placed, as
in Fi 5.
UIDAHO AVISTA Summs Rs.cn 2018
The last step of the project is to create Non-
Wire Solutions using open source analysis
tools such as GridLAB-D. A data flow
diagram, created to summarize how all the
chosen applications relate to each other, is
shown in Figure 6.
Figure 6. Project Data Flow
Blazegraph, an open-source application, sorts
through the large amounts of data defining a
distribution system. The software operates
through queries to navigate the CIM data
structure and extract specific information as
requested by the query at hand.
An example of one of these queries is shown in
Figure 7. It requests power flow information
at a low level distribution node.
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Figure 5. PowerWorld Illustration Figure 7. Blazegraph Query
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GridIAB-D, is an open-source application that
is used in simulating the performance of the
distribution grid. An excerpt of Gridl-AB-D
code is shown in Figure 8. Almost all of the
data is gathered in this format through
numerous parallel instantiations that extend
the lines of code into the hundreds of
thousands.
obJ.ct Etlr Ire F$enexalarL';
Dlarcr.llCN,'rieL rcI.t.gr l26i;
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LEEeFaL IC';
fi.Lr ploE ! Iopqt_Vol,tlEe.Plt,'
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Figure 8. GridLAB-D ExcerPt
Once a Gridl-AB-D simulation executes, the
program outputs an XML file shown below in
Figure 9. This output displays without any
additional edits from the user. What is shown
is the explicit version of the source (even
though all of the data is contained within this
page). Figure 10 shows the line of code that
causes this problem. This line of code must be
edited in the raw form of Figure 11. An
unknown character causes the XML file to face
an error when generating the output.
Figure 9. XML Output 1/3
Figure 1O. Unknown Character(s)
Figure 11. Raw XML
Following the editing of the XML file, Figure
12 becomes the current form of the XML. This
output is still illegible and requires one final
step. The problem with this code can be
traced back to a hyperlink to a missing page
(where the stylesheet was stored at one
time). The line of code shown in Figure 13.
originates from Figure 11. This error is fixed
by downloading the correct file to the local
system, and referencing the local directory
file location. Once this is changed, the output
changes to the format shown in Figure 14.
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6-q^ -@^iq ^ +q\a qlr i
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Figure 12. XML Output 2/3
Figure 13. Incorrect Style Sheet
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Figure 14. XML Output 3/3
One of the drawbacks to GridLAB-D however is
that it lacks a graphical user interface. The
work conducted within the system relies on the
use of a command terminal and various
commands that can produce output of the grid
analysis. While this is beneflcial for the sake of
analytics, a visual image was desired to
demonstrate the information at hand.
However, due to the constraints of the missing
overhead lines, the system was summarized to
Figure 15.
Figure 15. Simplified BLU/OGA System
Figure 16. shows what occurs once the data
from BLU 321 and OGA 611 is inputted into
GLM Plotter. The result reflects what occurs
after increasing the gravity aspect of the
visualization which pulls the image into this
shape. The leftmost points are that of the
transformers which connect to the larger
congregation of dark black nodes that are the
secondary sides of the transformers within
the total system. However, the large
remaining mass to the right side of the image
are the remaining nodes missing the
overhead lines connections and cannot be
processed by Gridl-AB-D.
To complete the system model and enable
GridI-AB-D to complete the Non-Wire
Solution, models for these overhead lines
were estimated in response to Blazegraph
queries. This modeling was pefformed in
coordination with research teams at
Washington State University and at PNNL. An
Excel tabulation and formatting of this data
can then be pasted into GLM files as shown in
Figure 17.
We prepared a User Guide that specifies and
illustrates these procedures in detail.
CmUncd_BLUE_OGA.glD
Figure 16. BLU321 and OGA611 Nodes
Figure 17. Manual Conversion
IV. RESULTS
The team recommends that GridLAB-D not be
used for analysis by Avista@ at this time. While
it shows potential to be a powerful tool usable
for large scale grid analysis in the future, it is
not currently suitable at this time. Should thesoftware be utilized again, the team's
deliverable of a User Guide outlines much of
the installation and an outline on operations of
the software up to July 2018.
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V. LESSONS LEARNED
a Ensure that the files that house the
necessary system data are compatiblewith the proposed software. This
slowed the project to a crawl and, in the
end, limited what could be done in thetime allotted. This is a general
comment that should be considered on
every project that is dependent on
existing data to properly model and
simulate any system.
Software with limited guides, e .g.,
GridlAB-D, can create challenges when
learning the software. This is one of the
hazards of some open-source software.
Multiple forms of software installation
without timestamps and or publication
dates can become confusing rather
quickly for developers.
Documenting all stages of software
related business is helpful both for
those developing, and those who will
utilize said developments.
Error correction can be difficult to
overcome when working with limited
documentation provided for the open
source software. Turn off error
correction when writing software.
Sometimes getting software running
takes the most time, and running the
software is easier.
a
a
a
a
a
VI. PATH TO MARKET
GridLAB-D is open source, so its appeal is high
because it has no cost. If it were fully
developed, it could contend or even replace the
likes of OpenDSS and PowerWorld as a free
alternative. Gridl-AB-D and other supplemental
software will be marketable following software
patches which reduce if not eliminate bugs
involving: file conversion, general operation,
and guides for more recent editions. GridlAB-D must gain a great deal of reliability and
sustainability if it is to form the basis of furthereffort to develop marketable tools and
software as proposed for this project.
ct
APPENDIX I
Two-Page Report: Aerogel Phase 2
fr:tnsra X
Universityotldaho AEwsrfr
College of Engineering
High Energy Efficient Aerogel-Glazing Coupled with
Aerogel-Insulated Walls in Residential Buildings: Phaseu
Project Duration: 12 months Project Cost: Total Funding $82,873
OBJECTIVE
The PIs validated the thermal conductivity of
the aerogel blankets in Phase I and found it to
be very low as close to 0.014 Wm-1K-1, which
confirms that aerogel blankets could be
considered a super insulator. The proposed
work will be based on experimental laboratory
testing (Dr. Ahmed Ibrahim), ANSYSMultiphysics simulation including
computational fluid dynamics (CFD) (Dr. Xing
and Dr. Sean Quallen), and EnergyPlus (Drs.
Ibrahim, Xing and Johnson). The team is
proposing to develop full detailed 3D single
family house simulation to capture the
thermal performance of walls insulated with
aerogel blankets and aerogel-based windowpanes. A practical tool for energy
consumptions' alternatives will be developed.
BUSINESS VALUE
It is anticipated that the use of Aerogel-based
window panes reduces the heat transfer
across building envelopes and therefore will
significantly reduce the annual heat loss
compared to the currently used window
material(s). In addition, a life cycle cost
analysis with a full consideration of service
life-cost will be performed and compared to
the performance of conventional insulation
materials.
Benefits to Avista: 1) Huge projected energy
saving: the team performed a preliminary
analysis on the proposed aerogel-based
glazing and found that heating saving is
estimated to be 15o/o when using one layer
(0.4-inch) of aerogel insulation in a window
and a wall of a typical building, and 2) Tool to
assess energy consumption and potential
saving and that will be based on parametric
studies using the validated numerical
simulations to quantify the various energy
leakage sources and optimize the design of
the windows and walls.
INDUSTRY NEED
Energy sustainability is a crucial issue for the
humanity's development in modern era,
which can significantly impact future quality
of life and the environment. The industry ismoving towards the construction of
sustainable-energy efficient buildings. The
outcomes of the current research will have a
direct impact on Avista customers saving
energy, reducing need for natural gas and
electricity. The Aerogel-based windows willbe efficiently used in retrofitting existing
structures and in new constructions as well.
BAGKGROUNDThe investigators have conducted a
comprehensive literature survey for the up-
to-date studies related to the performance
and implementation of aerogel-based glazinginsulation in residential buildings.
Representative publications are listed below:
l.Ghoshala, S., Neogi, S. (2OL4). Advance
Glazing System - Energy Efficiency Approachfor Buildings a Review, Energy Procedia 54
(2Ot4) 3s2 - 3sB
2.Cinzia Buratti, Elisa Moretti Transparent
insulating materials for buildings energy
saving: experimental results and performance
evaluation, Third International Conference on
Applied Energy - 16-18 May 2011 - Perugia,
Italy
3. High Energy-Efficient Windows with SilicaAerogel for Building Refurbishment:Experimental Characterization and
Preliminary Simulations in Different Climate
Conditions
SCOPE
The scope of this project is mainly focused on
evaluating the ability of the Aerogel-based
windows to save energy through:
Task 1: Literature Survey
Various studies have reported on the
characterization of Aerogel, along withpreliminary investigation of its
implementation as a super insulator,
(Ghoshala, S., Neogi, S. (2014)., Cinzia et al.
(201 1).
Task 2: Aerogel Acquisition
The team has purchased 54 ft2 of the Aerogel
based glazing. The panes have a 16mm
thickness. The team also purchased acomputer workstation for the CFD
simulations.
Task 3: Experimental Study
Dr. Ibrahim has staded field data collection.
Twenty thermocouple sensors have been
attached to the cubical scaled room as shown
in Figure 1. The scaled room was completely
sealed and the internal temperature was
raised up to 950F and then the decay in
temperatures was measured. Figure 2 shows
Temperature vs. time for the vertical walls.
The results will be used to verify the
computer simulations.
Task 4: Modeling and Simulation
Dr. Tao Xing, and Dr, Sean Quallen are using
computational fluid dynamics (CFD) to
simulate a cubical scaled room built using the
Aerogel panes.
Figure 1: View of cubical scaled room
*T*, "
Figure 2: Temperature versus time for the south
wall
The results of the CFD simulations have
helped to determine an expected convection
transfer coefflcient inside our experimental
domain as well as helping to determine ideas
The information contarned in this document is proprietary and confidential.
for temporal and spatial discretization forfuture simulations. These results also
demonstrate that the transition to a natural
top-to-bottom temperature gradient happens
rapidly, especially relative to the 1-2-hour
experimental timeframe (see Figure 3).
Figure 3: 2D simulation showing temperature
distribution at t = 0s (left), t = 30s (middle), and t
= 90s (right)
Task 5: Energy Simulation: will staft on 5/2Ot9
Task 5: Cost Analysis: will stat on 6l2ot9
DELIVERABLES
The main deliverable of this project will be a
final report includes all the experimental data
the data and the computer simulations, cost
analysis to compare the cost saving of the
insulation panes.
PROJEGT TEAM
SGHEDULE
A.ro3d
!.8
E
!tt
PRTNGIPAL TNVESTTGATOR(S)
Name Ahmed Ibrahim
Oroanization Universiw of Idaho-Civil Enoineerino
Contact #208 885 1328
Email [e-mail]
Name Tao Xinq
Orqanization University of Idaho-Mechanical Engineering
Contact #208 885 9032
Email xino(Ouidaho. edu
Name Brian lohnson
Oroanization
Contact #208 885 6902
Email biohnson@ uidaho.edu
RESEARCH ASSOGIATES/ ASSISTANTS
Name Sean Ouallen
0roanization universitv of Idaho- Mechanical Enoineerino
Email [e-mail]
Name Santu Golder
Oroanization [Jniversitv of Idaho-Mechanical Enoineerino
Email oold3752@vandals. uidaho.edu
TASX ?ITE
ALLOCATEI'
START
DATE
FIN!SH
DATE
{Task 1: Literature
review){5 Months}{t2/2018)
{Task 2: Material
pu rchasi nq ){2 Months}{9/20 18}{1 1/2018}
{Task 3: Computer
Validation){3 Months}{t2/20t9){212019}
{Task 4: Simulation}{6 Months}{2/2019){s/2019}
{Task 5: Energy
simulation {1 Months}{s/20 1e}{6120ts)
{Task 6: Cost
Analvsis){2 Months}{6/20 1s}{8/2019}
I t'
tJniversitv of Idaho-Electrical Enoineeri no
{9/20 18}
APPENDIX J
Two-Page Report: IR Camera
fr-trtsra X
University olldaho
Coltege of Art and Architecture
Using IR Cameras in Building Controls
AHutsrfi
Project Duration: 12 months Project Cost: Total Fundi ng $46,678
OBJEGTIVE
This project will demonstrate the feasibility of
using a low-cost infrared camera to estimate
the mean radiant temperature in a room. This
radiant temperature information is used to
more effectively heat and cool buildings. Over
the course of this study, the team will set up a
camera in an experimental chamber and
collect data from various scenarios. Once
collected, the team aims to process the datainto a comfort prediction and send that
information as a standard control signal.
Energy models will be used to estimate the
potential energy savings of incorporating an
infrared camera into building thermostats.
BUSINESS VALUE
Managing office temperatures by factoring in
the surface temperatures would allow for wider
air temperature setpoints, thus saving energy
each year. Increasing the cooling setpoint by
5oF has been shown to reduce total HVAC
energy by 27o/o. If the IR camera can
successfully detect both surface temperatures
and occupancy, then the need for additional
occupancy sensors could be eliminated and
this device can serve both purposes. If it is
successful in detecting glare in a room, it could
potentially serve in the role of a photosensoras well. The adoption of IR-enhanced
thermostats provides a holistic sense of
occupant comfoft that enables offices to
maintain efficient environments that improve
worker productivity.
INDUSTRY NEED
Most buildings manage their heating or cooling
based solely on zone air temperature. Even
when the thermostats are kept within a narrow
band of 4oF, occupant complaints persist
(Arens, et al., 2010). A large factor of human
comfort is being missed in conventional
thermostats: the inclusion of the mean radiant
temperature. While surface temperatures are
widely used for predicting human comfort,
rarely are they directly used in building
controls. A control system that incorporates
the surface temperatures of a zone would allow
for a wider range of supply air temperatures
and better meet the needs of occupants. The
wider range of air temperatures would reduce
energy consumption and help to capitalize on
operational features such as natural
ventilation, night-flush and optimized set-
points.
BAGKGROUND
Many previous studies have established thatthe surrounding surface temperatures are
more important to human comfoft than the air
temperature (Olesen 2007). Standard comfort
predictions require both the air and surface
temperatures, yet surfaces are rarely used in
building controls. Surface temperatures can be
measured with globe sensors, IR beams, or
thermocouples, each of these methods has
drawbacks of cost and complexity. With the
recent reduction in cost of IR technology, low-
cost cameras could provide an alternative.
SGOPE
The research team has set up an experimental
chamber with an IR camera that has been able
to accurately estimate surface temperatures to
within 1oF. These readings have been used to
calculate the impact that each surface's
temperature might have on a hypothetical
occupant. Energy models of the test chambers
have been created to estimate energy savings
of enhanced thermostat controls. At the end ofthe project, the research team will have
developed a method to take a photo of a room
using a low-cost IR camera and from that data,
predict occupant comfort. That information will
be sent out as a standard control signal which
could be read by a typical HVAC system.
Task 1: Project Planning and Reporting
Conduct team meetings and ongoing project
updates, repofts and deliverables as requiredby Avista staff, project management
contractors, and the PUC. This task continues
th roughout the project.
Task 2: Set up Experimental Chamber
The team will deploy instruments in a test
chamber at the U of I IDL site to monitor all
surface temperatures, air temperatures, light
levels, and COz levels.
Task 3: Deploy lR Camera in Chamber
IDL will set up the camera to take pictures at
different angles and send the digital files to a
computer for analysis to determine the ideal
settings and method for MRT measurement.
Task 4: Collect Operational Data
The research team will use different setpoints
for the HVAC system and occupy the room at
different times over a period of several weeks
to establish baseline data.
Task 5: Develop Algorithm for Processing
Measurements
In parallel with Task 4, IDL will use the ongoing
operational data collection to correlate the IR
camera files to readings of temperatures,
lighting, and occupancy.
Task 5: Translate lR Camera Files to BACnet Signals
The IDL team will develop a process to
translate IR measurements into a BACnet
signal that could be used by any controller.
Task 7: Estimate Savings
The team will use energy simulation results to
compare the energy impacts of using an IR
camera to manage controls versus traditional
control signals (air temperature and COz) over
a sample period.
Task 8: Develop Workflow for Practitioners
The final task will be to detail the methods of
how to set up an IR camera for monitoring
occupancy and surface temperatures and how
those signals can be translated into building
control networks. This will ideally inspire
futher commercialization of this concept and
result in energy savings once implemented.
This documentation will be submitted to an
academic journal.
DELIVERABLES
. The team has completed a current
literature review of the relevant
technology in this sector.. The team has prepared a test chamber
for data collection with a mounted IR
camera that is able to read the suface
temperatures to within 1oF of accuracy.. The camera and chamber have been
used to collect a set of data that
includes variations in the following
categories: air temperatures, suface
temperatures, occupancy, and lighting.. The team has determined a set of
equations that will allow the IR camerato estimate the mean radiant
temperature at a location in the room.. The next deliverable (not yet complete)
is the ability to send a measurement of
predicted occupant comfort as a
standard control signal.. The team will estimate energy savingsfor typical small commercial offlce
buildings in the Pacific Northwest. Documentation will be written on how
to use an IR camera to record surface
temperatures and provide an overall
verification of the proof of concept for
this technology.
PROJECT TEAM
SGHEDULE
PRTNGTPAL TNVESTIGATOR(S)
Name Damon Woods
n Universitv of Idaho Inteorated Desion Lab
Contact #(204) 364-462t
Email dwoods@ uidaho. edu
RESEARG}I ASSISTANTS
lubin Mathai
Oroanization Universitv of Idaho Inteorated Desion Lab
Emai iubi 53 1 2@vandals. uidaho.ed u
TASK
TtTE
ALLOGATED
(tonltls,
START
DATE
FINISH
DATE
Proiect Plannino 1-2 09lol/78 08/30/t9
Set uo Exo Chamber 2 09/01/18 rol26lt8
DeDlov IR Camera 2 70/07/78 tt/ 16/ta
Collect Data 2 72/07/18 0Lt25tL9
Develop Alqorithm 4 ou2sl19 os/241t9
Translate Ctrl Siqnal 3 o3t0Lt19 06t2LtL9
Estimate Savinqs 3 o4l29l19 061261t9
Develoo Workflow 2 07/ot/t9 o8lt6lt9
The information contained in this document is proprietary and confidential,
APPENDIX K
Two-Page Report: All-lron Battery
#rutsra X
Universityotldaho AHwsrfr
College of Science
Proof of Concept All-Iron Battery with Carbon Electrodes
Project Duration: 10 months Project Cost: Total Funding $48,141
OBJEGTIVE
This project objective is to refine an extremely
low-cost, non-toxic, non-flammable battery
chemistry. This battery stores energy using an
iron anode and an iron salt cathode. A new
carbon electrode material developed in the
Cheng lab at the University of Idaho is being
used to increase performance. The primary
advantage of the iron/carbon design is a low
price per Watt-hour of storage. Our current
results suggest that this chemistry will be
economical for stationary applications. We are
building a demonstration battery and are
planning to spin out a company to
commercialize its production.
BUSINESS VALUE
A safe and inexpensive battery could help
expand the use of low-cost renewable energy.
Energy storage also enables energy arbitrage.
INDUSTRY NEED
Expansion of renewable energy capability has
resulted in periods of oversupply; when more
energy is generated than can be used
generators are forced to shut down. In sunny
locations like Mexico, solar energy can cost as
little as $14 per megawatt hour. Prices in the
Pacific Northwest are approximately $30 per
megawatt hour. This represents an economic
opportunity in energy arbitrage: if oversupply
of renewable energy could be stored and sold
during peak demand, it would provide a new
revenue source. In the long term, this will also
increase overall demand for the expansion of
wind and solar energy. However, there is no
stationary battery technology that is
sufficiently safe and inexpensive to make a
practical grid storage solution. Cost is the
critical factor for a stationary battery. Weight
and volume are less important (unlike in
mobile applications). The extremely low-cost,
non-toxic, non-flammable all-iron battery can
help meet this need.
BACKGROUND
Prior to Avista funding, the Iron battery was a
crowdfunded effort to make an "Open Source"
energy storage solution. The Allen lab
screened iron salts and separator materials for
low cost and high reliability. Avista funds have
allowed for optimization and scale-up of the
preliminary cell.
The overall cell is shown above. An iron anode
is oxidized at the left. This produces electrons
that flow to the right and react with iron (III)
sulfate. We started with a 20 ml cell made
from iron, iron (III) sulfate, and a polymer
separator.
SGOPE
Task 1: Collect data on 20ml cell
The project started with a prototype 20 ml cell which was
not fully characterized. We replaced the inexpensive
polymer (sodium polyacrylate) with Nafion (a commercial
separator). We also refined assembly methods to make a
sealed cell that lasted far longer than our original design.
We characterized the resulting cell and found that it
delivered -10 mW of peak power. lt also could be
charged and discharged dozens of times with little loss in
capacity.
Load
o(!
L(I,o-(Urll
+
c)tl-
I oa
Task 2: Construct 200 ml cell
(Fel
C.rbon Eh
etho&
{c}
.-
The 200 ml cell is a scaled version of the 20 ml cell. A
plastic bag holds the "pouch" separator membrane. The
pouch separates the interior (anode) from the exterior
(cathode) electrolyte. The diagram above shows an
assembled prototype. The first assembly procedure
produced pinhole leaks in the plastic. The current
assembly procedure produces a cell without leaks.
Task 3: Characterize 200 ml cell
0.6
0 Time (hours) 30
The initial characterization of the 200 ml cell produced
close to the desired total energy capacity but a low total
power. The discharge of the cell takes 24 hours (as
above) or longer. Cell improvements to meet the desired
power requirements (1W) include alternative
membranes and conductive additives (e.g. GUITAR
carbon) to the electrolyte solutions.
Task 4: Build 1t battery
The 1 L battery will consist of five of the 200 ml cells
connected in series. We have constructed a housing to
contain the cell stack. lmages of the prototype (left) and
final acrylic (right) are shown above.
Task 5: Characterize 1L battery
The performance of the 200 ml stack will yield
performance benchmarks for the 1L cell. The
The informalior contained in this document is proprietary and confidential.
performance objectives are a 15 Wh capacity
and 15 watts of peak power.
Task 6: Prepare follow-up proposal
Options in the table include SBIR funding and
private capital. We need to reach our goals
for power and energy capacity.
DELIVERABLES
. Construct a 0.2 L cell (complete). 0.2 L cell stores 0.4 Wh (goal 1.5 Wh). O.2 L cell delivers 40 mW (goal 1W)
o Construct a 1L battery (in progress). 1 L cell should store 15 Wh of energy. 1 L cell should deliver >5 W peak power. Apply for SBIR and/or propose venture
funding for commercial production. Report on appropriate path to market
PROJECT TEAM
SCHEDULE
TASX TINE
ALLOGATED
START
DATE
FINISH
DATE
Collect data on 20ml cell 1 9t18 10/18
Construct 200 ml cell J 10t4 1t19
Characterize 200 ml ell 1119 3/ t9
Build'lL batterv 2 3/19 5/19
Characlerize 1 L betterv 5/19 7t19
Preoare follow-uD orooosal 1 7t19 8/19
E
cq)
oCL
PRTNGTPAL TNVESTTGATOR(S)
Name Peter Allen
Orqa n ization University of Idaho
Contact #208-885-5807
Email [e-mail]
Name (Co-I) Francis Cheno
Orqanization University of ldaho
Contact #
Email
Name (Co-I) Dean Edwards
Oroanization [Jniversitv of Idaho
Contact #
Email
RESEARGH ASSISTANTS
Name Nicolas Yensen
Orqanization University of Idaho
Email
Name Depak Koirla
Oroanization L,niversitv of Idaho
Email
Name
Oroanization Universiw of Idaho
Email
Fe-
7 --q
Ei;4
APPENDIX L
Two-Page Report: Energy Trading System
Aiusra #
"7
Universityotldaho AYr-stsrn
College of Engineering
Designing and Evaluating an Energy Trading System for
Prosumers
Project Duration: 12 months
OBJEGTIVE
The objective of this project is to analyze and
develop a prototype system that would enable
Avista prosumers and consumers to trade
power on-demand with utility oversight or withthe utility while also ensuring the utility's
network resilient operation with respect to the
enablement of such prosumer-consumer
transactions. A prototype software system will
be designed and developed that enables therequest of prosumer-consumer energy
transactions through an online web and/or
application interface. In addition, a system for
evaluating the feasibility of the proposed
transactions within the Avista distribution
network will be developed and integrated.
Such type of integrated system would enable
Avista to develop a new market for prosumer-
consumer power trading and also to plan,
manage, and control such market and the flow
of power through its network.
BUSINESS VALUE
Avista will benefit from such prototype in the
following ways:
. Provide a platform for testing new
technologies and algorithms that would
enable larger scale implementations of
such customer-driven trading markets. Enable the collection of data on sharing
behaviors and trading patterns,
. Enable data analytics that may lead to
increased efficiency in the distribution
system,. Enable data analytics that may lead to
adequate and profitable electric power
pricing strategies for prosumers and
smart-grid enabled consumers and
Avista power transaction fee structure.
Cost: Total funding
INDUSTRY NEED
The adoption of consumer-level electric energy
production and storage and of smart consumer
appliances is accelerating. Examples of
technologies leading this rapid adoption are
photovoltaics, small wind, electric vehicles,
and smaft water heaters and freezers, amongother technologies. Within such a new
prosumer-enabled Smart Grid, enabling the
managed but timely and selective trading and
transmission of power between prosumers
(producer-consumer) and with the utility, with
utility oversight may enable a more efficient
use of the Power Grid as well as provide utility
savings on generation and transmission. For
example, a temporary increase in demand
from a smart-grid-enabled customer could be
served from a grid-near prosumer with stored
capacity or current wind or solar generation.
BACKGROUND
The following is an example of how the
proposed prosumer-consumer power trading
may work. One of Avista's customers installs
solar panels or has a storage system such as
an electric vehicle and generates or stores
electricity. To sell some of this prosumer's
excess electricity, this prosumer goes to an
Avista-managed website and enters the
amount of energy that they want to sell, the
target price, its nature, and other constraints
such as timing. An Avista customer needs
some additional electricity at a given or
scheduled time. Such customer goes to the
same website and indicates an interest in
buying energy under certain conditions,
pricing, and time period. The proposed system
then creates a match between the prosumer
energy offers, requests, restrictions, timing,
and pricing, informs the customers, enables
and records the business transaction.
TASKS and STATUS:
Task 1: System Requirements
Research has been completed in determining
the desired system architecture and modeling
packages. OpenDSS will be used for modeling
the power system.
Task 2: Database Design
Design and model the system using modern
system modeling tools such as ERD.
Completed design an implementation to
support transactions. Refinements are neededto fully suppoft the Power System Model
interaction.
Task 3: Database Architecture
Develop the database architecture and schema
and select a DBMS. Completed as needed for
initial prototype. Refinements are ongoing.
Task 4: Security Risks
Analyze security risks and design and
implement security mechanisms. Ongoing as
i m plementation proceeds.
Task 5: Simulation Model
The IEEE 13 bus distribution model will be used
for testing functionality. A model has been
modified to include Photovoltaics, battery
storage, electric vehicles, wind, and switch
gear. This model will be used along side test
cases for PV to test the application software.
Task 6: Web Inteface
Design and sketch Web and/or App interfaces:
User and Administration. Prototype system is
complete. Enhancements are ongoing as
needed.
Task 7: Prototype Software
Build the prototype software. Prototype
system is complete. Enhancements are
ongoing as needed.
Task 8: Transaction ControlThe communication between the web
application and OpenDSS has started and is
being interfaced through a SQL query and
Python. The team has the individual pafts: SQL
Query, OpenDSS, and Python in the testing
phases.
Task 9: Functionality Testing
The team has started testing individual pieces
of the software. Communication between
python and OpenDSS has been established,
and the next steps are to incorporate the SQL
query and database transactions.
Task 1O: Usage Guides
This task will be performed after Task 9.
Task 11: OpenDSS Test Case
Three test cases are being explored for
implementation in OpenDSS. These cases are
primarily for different time scales such as: one
day, one week, one month data sets to provide
enough Solar and customer data for testing.
DELIVERABLES
The deliverables on successful completion in
this project including the software prototypes
will be:. Written final report of the results of
these studies in the format approved by
Avista.. Interim reports and online conferences
with Avista. Mid-term report.. Proof-of-concept software and user and
admin istrative documentation.. Proof-of-concept evaluation within a
small-scale simulated transmission and
distribution system.. Outlines of proposals for follow-on
funding to further develop and refine
the prototype.
PROJEGT TEAM
SGHEDULE
PRINCIPAL INVESTIGATOR
Name Dr. Yacine Chakhchoukh
Contact #208-885- 1 550
Email vacinec@ uidaho.edu
CO.PRINGIPAL INVESTIGATOR
Name Dr. Brian lohnson
Contact #(208) 88s-6902
Email biohnson@ uidaho.edu
Name Dr. Herbert Hess
Contact #[phone]
Email hhess(Auidaho.ed u
Name Dr. Daniel Conte De Leon
Contact #208-885-6520
Email b'iohnson@ uidaho.edu
Name Dr. Hanotian Lei
Contact #208-885-0952
Email hleiT(ou idaho. edu
Task
Item
Start Date Finish
Date
Yo
Completion
Task 1 09t01t18 11t01t18 100%
Task 2 09/ 01/18 11t01t18 100o/o
Task 3 09/ 01/18 01t01t19 100o/o
Task 4 09/ 01/18 01to1t19 30Yo
Task 5 09/ 01/18 01t01t19 100o/o
Task 6 09/ 01/18 01t01t19 600/o
Task 7 09/ 01/18 03/01/19 40%
Task 8 01t0'U19 06/01/19 10o/o
Task 9 01t01t19 08/01/19 5%
Task l0 08/01/19 08/31/19 0o/o
Task 11 01t14t19 02t14t19 70o/o