20071026Tucker rebuttal.pdf

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ZDfil OCT 26 AM 10: 49
IDAHO PUBLIC,
UTILITIES COMMISSIOI'
BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION
IN THE MATTER OF THE
APPLICATION OF ROCKY
MOUNTAIN POWER FOR APPROVAL
OF CHANGES TO ITS ELECTRIC SERVICE SCHEDULES
CASE NO. P AC-07-
Rebuttal Testimony
of Mark E. Tucker
ROCKY MOUNTAIN POWER
CASE NO. PAC-07-
October 2007
Please state your name, business address and present position with the
Company (also referred to as Rocky Mountain Power).
My name is Mark E. Tucker. My business address is 825 NE Multnomah, Suite
2000, Portland, Oregon 97232, and I am currently employed as a Cost of Service
& Pricing Analyst in the Regulation Department.
Are you the same Mark E. Tucker that previously submitted testimony in
this proceeding?
Yes I am.
Purpose of Rebuttal Testimony
What is the purpose of your rebuttal testimony?
In my rebuttal testimony I present the Company s Class Cost of Service Study
based on a twelve month historic test period ending December 31 , 2006, that has
been updated to correspond with the Company s rebuttal filing regarding revenue
requirement in this case. Additionally, I respond to the testimony of Monsanto
witness Ms. Kathryn Iverson, Idaho Irrigation Pumpers Association (lIP A)
witness Mr. Anthony Yankel, Idaho Public Utilities Commission Staff witness
Mr. Bryan Lanspery, and Agrium witness Dr. Dennis Peseau.
Summary of Results
Please explain Exhibit No. 51.
Exhibit No. 51 is the summary table from the Company s Class Cost of Service
Study for the State of Idaho. It is based on the Company s revised annual results
of operations for the State of Idaho presented in the rebuttal testimony of
Company witness Mr. Steven McDougal and reflects all of the revisions and
Tucker, Di-Reb -
Rocky Mountain Power
corrections described in his testimony and in my rebuttal testimony. Page 1
presents results based on the Company s December 2006 rate of return assuming
current rate levels. Page 2 shows the results using the return provided by the
Company s requested $15.4 million price increase.
Rebuttal of Ms. Kathryn Iverson
Do you agree with Ms. Iverson that the cost of service study provided in
response to Monsanto Data Request 9.6 should be the starting point before
making any additional adjustments?
Yes. The Company agrees with the correction related to the calculation of
Monsanto s peak demand in the cost of service study. This adjustment is included
in the cost of service study that accompanies my rebuttal testimony.
Do you agree with Ms. Iverson s testimony that the demand and energy
totals that are used for jurisdictional allocation purposes do not match the
sum of the class loads used in the cost of service study?
Yes. However, the jurisdictional loads and the class loads in the cost of service
study are calculated in different ways and will not match exactly. The Company
explained this difference in its response to lIP A Data Request 1.3. Two types of
data are utilized in the calculations. For the jurisdictional allocation, the
jurisdictional load data is derived from measured loads at several metering points
usually at the generation level. For the class allocation in the cost of service
study, class peak load data is collected at the sales level and adjusted up to the
generation level using historical average annual loss factors. Differences between
the two are expected. Both load calculations are accurate for the purposes for
Tucker, Di-Reb - 2
Rocky Mountain Power
which they are used, and it is not necessary for them to match exactly.
Do you agree with Ms. Iverson s proposal that the estimated class loads be
adjusted up so that they match the metered loads used for jurisdictional
allocations?
No. In the past, the Company has adjusted class peak loads in some jurisdictions
to match the jurisdictional loads, as recommended by Ms. Iverson, but stopped
doing so after a Load Research Working Group investigated this issue in 2001-
2002. The Working Group, which was convened by order of the Utah Public
Service Commission in Docket 01-035-, included the Company and multiple
intervenor groups in Utah. It concluded that adjusting the class loads in the cost
of service study created new problems and that the practice should be
discontinued. Concerns raised by the Working Group centered on the fact that
only the estimated load customers were affected by the adjustments. Members
agreed that the variance between the jurisdictional loads and the class cost of
service loads could be caused by the estimated load data, the metered
jurisdictional load data, or the census data, and that adjusting just one of these
components was inappropriate. The assumption that the variance was due to the
load research estimates could not be supported after a thorough review of the data.
The adjustments in some cases created large swings in cost allocation and this
placed unfair cost burdens on some customer classes. A copy of the Load
Research Working Group final report is provided as Exhibit No. 52.
Making the adjustment that Ms. Iverson proposes would increase the loads
assigned to the estimated classes (residential, irrigation and general service)
Tucker, Di-Reb - 3
Rocky Mountain Power
which would lower costs allocated to the other classes, especially Monsanto.
However, while this adjustment would produce better results for Monsanto, it
would not necessarily result in a more accurate or equitable cost allocation. The
Company believes the class load data in the cost of service study is the most
accurate data available and should continue to be relied upon.
Please explain Ms. Iverson s proposal to change the way the Revised Protocol
Rate Mitigation Cap is allocated to the classes.
Rather than view the impacts of the Rate Mitigation Cap as a reduction in the
Company s return on rate base, she views the Cap as a reduction in the allocation
of generation and transmission costs to Idaho. She recommends that the $3.
million Rate Mitigation Cap impact be reflected as a reduction to generation and
transmission revenue requirement.
Do you agree?
Not necessarily. The Rate Mitigation Cap does not reduce the allocation of costs
to Idaho; it limits the total revenues the Company is allowed to collect. This in
turn, lowers the rate of return the Company will actually realize in Idaho. Under
the Rate Mitigation Cap, the Company has agreed to accept less than the full
revenue requirement it might otherwise claim, which should be viewed as a
reduction in the return to shareholders. It is appropriate under those terms to
reduce the rate of return equally across all functions as the Company has done.
The Company s cost of service study reflects the impact of the Rate Mitigation
Cap by incorporating the lower "effective" return on rate base it produces.
The stipulation signed by all parties, including Monsanto, in the Multi-
Tucker, Di-Reb - 4
Rocky Mountain Power
State Process (MSP) docket (Case No. P AC-02-3) states that the Cap will be
applied to "the Company s Idaho revenue requirement to be used for the purpose
of setting rates for Idaho customers." Similarly, the final Commission order in
the MSP docket refers to the cap being applied to "Idaho rates" and "revenue
requirement calculations." The concept of applying the cap to specific functional
areas does not appear in the stipulation or order. The Company s method of
applying the Cap used in this case is consistent with past practice in Idaho and
Utah, which has a similar Cap in place. Ms. Iverson s approach is a departure
from the traditional view that all business functions are producing the same rate of
return. Because Idaho does not have unbundled rates, the Company has
functionalized costs but not functionalized revenue. We have calculated
functionalized revenue for our cost of service studies in such a way that all
functions produce the same rate of return.
What is the impact of Ms. Iverson s adjustment?
I prepared a cost of service study that calculated the increase using the full
Revised Protocol increase, then functionalized the Rate Mitigation Cap as a credit
to the generation and transmission functions using the PT (Production and
Transmission Plant) functional factor, and allocated it to classes using the FI0
(System Coincident Peak) factor. The overall increase remained the same, but
about $896 000 of the Cap credit shifted from Distribution, Retail and
Miscellaneous to Generation and Transmission. This resulted in a decrease to
Monsanto s revenue requirement of about $335 000 and a decrease to Agrium of
about $23 000; the residential class saw a revenue requirement increase of about
Tucker, Di-Reb - 5
Rocky Mountain Power
$206 000 and the irrigation class increased by about $160 000. The other classes
were affected to a lesser degree. Page I of Exhibit No. 53 shows the Functional
Summary sheet from this revised cost of service study. Line 67 shows the Rate
Mitigation Cap credit and the amount allocated to each function. Page 2 shows
the Summary page from the cost of service study.
Is this a reasonable adjustment?
Yes. Should the Commission desire to mitigate the impacts of the movement to
full cost of service for the special contract customers, this adjustment provides a
reasonable basis for doing so and the Company would support it for that purpose.
Rebuttal of Mr. Anthony Yankel
Do you agree with Mr. Yankel's testimony that the impact of the irrigation
load control program is not fully represented in the Company s load
research sampling?
No. While the irrigation class is particularly hard to sample due to crop rotations
and weather patterns that cause the class as a whole and individual farms to vary
their usage greatly from year to year, the Company believes that the load data in
the current cost of service study accurately reflects the loads placed on the system
by the irrigation class. A site that was selected as representative of a certain user
type in one year may have completely different characteristics the following year,
and even different characteristics the year after that. The load control program
has similar complications since participants only sign up for one season at a time
and continuing participants may not be curtailed at the same day and time from
year to year, or may not choose to participate from one year to the next.
Tucker, Di-Reb - 6
Rocky Mountain Power
Notwithstanding these challenges, PURP A standards for load research
specify that load research samples be designed to achieve plus or minus 10
percent precision at a 90 percent confidence level. All of the Company s load
research samples meet this standard. The Company also performs statistical
checks to ensure that the load research data comports with known energy use.
addition, the Company has produced three cost of service studies in Idaho since
2004 using the current sample sites and methodology, and the studies have shown
consistent results for the irrigation class in terms of their cost of service. This
indicates the data and our methods are statistically accurate and reliable.
Do you agree with Mr. Yankel's conclusions and analysis regarding the
amount of curtailment included in the load research sample?
No. As stated in the Company s response to lIP A Data Request 1.20, the
irrigation load control program is well-represented in the load research sample;
about 20 percent of the irrigation class participates in the program, while about 33
percent of the load sample sites are load control program participants. Further
the stratified random sampling procedure that the Company uses produces results
that are designed to be analyzed as a whole. One cannot produce statistically
meaningful results by pulling out subsets of data and analyzing them in isolation
as Mr. Yankel does.
The load sample was designed to measure the load that the entire irrigation
class places on the system at the time of system peak, and the sample is designed
to do that within PURP A standards. It is an accurate measure of the load on the
system at the time of system peak, and any curtailment in effect at that time is
Tucker, Di-Reb - 7
Rocky Mountain Power
reflected in the load sample estimates within PURP A specifications.
Rebuttal of Mr. Bryan Lanspery
Do you agree with Staff witness Mr. Lanspery that the Company s load
sampling is inadequate for non-demand metered customers?
No. Our current samples have been designed to meet PURP A standards for load
research sample data as discussed earlier in my testimony. The Company has
agreed to add new load sampling meters to its residential load sampling program
by the end ofthis year, and to start rotating residential and irrigation load sample
locations starting in 2008. However, this should not be taken as an indication that
our current load sample does not meet PURP A standards. All of the load research
sample data presented in this case meets these standards. Load research sample
points are updated and rotated periodically in the normal course of business. Our
current load research data is accurate and reliable.
Rebuttal of Dr. Dennis Peseau
Do you agree with Dr. Peseau s assertion on page 8 of his direct testimony
that the Company s cost of service study is "quite different from any cost of
service studies recently offered in other proceedings before this Commission,
and also very different from the cost of service studies originally developed
by PaciflCorp in the 1970s -1990"
No. Dr. Peseau is referring to the Company s use of an unweighted 12 CP
allocation method to allocate demand-related generation and transmission costs.
The Company has used unweighted 8 CP and 12 CP allocation methods in Idaho
since at least 1984 (Docket U -1009-137) and perhaps longer than that. In the
Tucker, Di-Reb - 8
Rocky Mountain Power
Company s 1990 rate reduction case (UPL-90-1) the Commission stated a
preference for 8 CP and 12 CP methods and rejected the 1 CP approach preferred
by Nu-West because "it does not accurately reflect cost causation on UP&L'
system throughout the year and has the potential, ifnot the tendency, to produce
erratic results." The Company s methodology in this case is certainly not new
either to the Company or to this Commission.
Does the Company allocate all demand-related generation costs using this
unweighted 12 CP method?
No. The Company recognizes, as Dr. Peseau points out, that utilities incur greater
costs to serve during peak periods. For this reason, under the MSP Revised
Protocol approved by the Idaho Commission in Order No. 29708, our generation
resources are separated into system resources and seasonal resources and these
groups of resources are allocated to states and to classes separately.
Please explain the difference between system resources and seasonal
resources.
System resources are those resources that are used to meet most of the load across
the Company s integrated system. This is the bulk of the Company s generation
and it represents base and intermediate load plants. The cost of operating these
assets does not vary greatly throughout the year, and it is therefore appropriate to
allocate the costs associated with them on an unweighted 12 CP basis. Seasonal
resources, on the other hand, are resources such as simple-cycle combustion
turbine "peaker" plants and contracts that are only in effect for certain months out
of the year. These are resources that are used to meet the Company s peak load.
Tucker, Di-Reb - 9
Rocky Mountain Power
The costs associated with these resources are assigned to the months in which the
resource dispatches, and to the classes based on their share of total usage in those
months. In this way, the costs associated with those resources needed to meet
peak load are allocated more heavily on the classes that have higher'loads in the
peak months.
Why do you say that an unweighted 12 CP allocation method is most
appropriate for allocating system resources? Isn t RMP a summer-peaking
utility?
RMP is a summer-peaking utility, but costs are allocated based on the entire
integrated system because that is how our system is planned and dispatched. The
Company has used a 12 CP allocator for system demand costs since the Pacific
Power - Utah Power merger. During the MSP docket (P AC-02-3) the
Company revisited the stress factor analysis that was employed at the time of the
merger to determine if a 12 CP allocation method is still the most appropriate
method for the Company to use. The results indicate that all months contribute to
the system peak in some way and should be included in cost allocation. This
same issue was raised in the Company s 2001 case involving Monsanto s contract
rate (PAC-01-16), and Staff witness Mr. David Schunke endorsed the
Company s approach, stating on page 16 of his direct testimony, "A 12 CP
generation and transmission allocator better represents the actual system
operation. It recognizes that each of the monthly peaks is of importance.
In addition, we believe it is appropriate for the allocation methods to be
consistent for inter-jurisdictional allocations and for class cost of service
Tucker, Di-Reb - 10
Rocky Mountain Power
allocations. 12 CP is used for the allocation of system resources in the JAM as
agreed to in adopting the MSP Revised Protocol and should continue to be used
for class cost of service allocations.
Do other Idaho utilities use similar allocation methods?
In his direct testimony, Dr. Peseau refers to the weighting methodology that Idaho
Power uses as an example of a superior allocation method. In the past, Idaho
Power has used marginal generation cost in each month to weight the coincident
peaks in order to place more weight on loads occurring in the more expensive
months. However, in its current rate case (IPC-07-8) Idaho Power is proposing
to do away with this method, because, as cost of service witness Mr. Timothy
Tatum states on page 14 of his direct testimony, "There is potential to
disproportionately allocate fixed base and intermediate generation costs that do
not vary greatly between the summer and non-summer seasons to the higher cost
summer months." Mr. Tatum offers several allocation alternatives, all of which
use a combination of unweighted 12 CP for base and intermediate resources along
with a separate allocator for resources needed to meet peak loads, similar to the
method the Company employs.
Shifting fixed costs to the summer rnonths would benefit Dr. Peseau
client, but it would hurt the classes that are heavier summer users, particularly the
irrigation class. Dr. Peseau s proposed allocation methods would place
disproportionate weight on the summer months and could result in more volatile
results from year to year.
Tucker, Di-Reb -
Rocky Mountain Power
Is the Company s allocation method an acceptable way to allocate demand
costs?
Yes it is. The 12 CP method the company uses allocates demand costs in a way
that treats all classes equitably and should be retained in this case.
Workpapers
Have you included your workpapers?
Yes. An electronic copy of the cost of service model underlying the summary
tables in Exhibit No. 51 has been provided to all parties on CD.
Does this conclude your rebuttal testimony?
Yes.
Tucker, Di-Reb - 12
Rocky Mountain Power
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KtLotlV C:'
zunI OCT 26 fHi 10: 4~:~oN~~~-
07-
IDAHO PUBLIC Witness: Mark E. Tucker
UTILITIES COMMISSIOf';
BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION
ROCKY MOUNTAIN POWER
Exhibit Accompanying Rebuttal Testimony of Mark E. Tucker
Cost of Service Summary by Rate Schedule
October 2007
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ZOUl OCT 26 Ai'1l0= 49 Case No. PAC-07-
Exhibit No. 52
Witness: Mark E. TuckerIDAHO PUBLIC,
UTILITIES COMMISSIOI'
BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION
ROCKY MOUNTAIN POWER
Exhibit Accompanying Rebuttal Testimony of Mark E. Tucker
Load Research Working Group Report to the Utah Public Service Commission
October 2007
Rocky Mountain Power
Exhibit No, S2 page 1 of 19
CASE No, PAC-O7-
Witness; Mark E, Tucker
Load Research Working Group
Report To The
Utah Public Service Commission
1 July 2002
Rocky Mountain Power
Exhibit No, 52 page 2 of 19
CASE No, PAC-O7-
Witness: Mark E. Tucker
Table of Contents
Introduction.......................................................................................
:..............................
Executive Summary......................................................................................................... 2
Description of Load Research Techniques .....
............. ...........
................................. ........ 6
Quality and Reliability of Load Research Data
As It Relates to Calibration Adjustments............................................................... 9
Use of Load Research Data to Develop Residential Rate Design................................. 13
rrigation Load Research............................................................................................... 15
Appendix........................................................................................................................
PacifiCorp s Overview Presentation of its Load Research Program .................. A1
September 2000 Hourly Percentage Calibrations..............................................
September 2000 Hourly MWH Calibrations.......................................................
Utah September 2000 COS - Residential Split Summary..................................
Rocky Mountain Power
Exhibit No, 52 page 3 of 19
CASE No, PAC-O7-
Witness: Mark E, Tucker
Load Research Working Group Report to Utah PSG 1 July 2002
Introduction
In its November 2, 2001 Stipulation Order in PacifiCorp general rate case Docket No.
01-035-, the Utah Public Service Commission (Commission) established a Utah Load
Resource Working Group (Working Group). Membership was to be drawn from
PacifiCorp (Company), the Division of Public Utilities (Division), the Committee of
Consumers Services (Committee), and other interested parties. The Committee was
assigned to chair the group. The Commission directed the Working Group to review
PacifiCorp s current and planned load research and studies and submit its report of
findings and recommendations by 1 July 2002.
The Load Research Working Group met five times between January 2002 and June
2002. Representatives of the following parties participated at some or all or those
meetings: Commission Staff, the Committee , Crossroads Urban Center, the Division
, Hill Air Force Base , Salt Lake Community Action Program, PacifiCorp, and the Utah
Farm Bureau.
The Load Research Working Group addressed the following issues:
. The techniques used to collect load research data as well as some of the
practical problems associated with gathering reliable data.
. The quality and reliability of the load research data as it relates to
calibration/adjustments that have been performed on this data.
. The use of the load research data to help design residential rates for customers
that use more than 1 000 kWh per month during the summer months.
. The need to develop alternatives to the use of historical irrigation load research
data for rate case purposes on a going forward basis.
There was agreement within the Working Group on all issues that were fully reviewed.
For those issues that were not fully reviewed , there was general agreement on progress
achieved and what the data means that has been reviewed thus far. Although some
issues were not fully investigated because of time and other constraints, the Working
Group has been able to better define and clarify these issues so as to make future
discussions regarding these matters more focused with a clearer point from which to
begin.
Load Research Working Group Report to Utah PSG 1 July 2002
Rocky Mountain Power
Exhibit No, 52 page 4 of 19
CASE No. PAC-O7-
Witness; Mark E. Tucker
Executive Summary
In the Commission s Order of November 2 , 2001 it adopted a Stipulation that was
presented regarding PacifiCorp Docket No. 01-035-01. As a part of that Order and as a
part of the Stipulation a Load Research Working group was established to review the
current and planned PacifiCorp load research efforts. Although the Stipulation and the
Order did not specify concerns to be addressed, the Working Group focused upon
many of the concerns that were raised during the rate case that are associated with
load research data. The areas reviewed included:
. The quality and reliability of the load research data.
It was decided that with the addition of a large number of sample points for the
Residential Class in early 2000 , that the quality and reliability of the load
research data has been increased. There is still a question about quality and
reliability related to the fact that there is wholesale movement of sample
customers between stratum boundaries on a monthly basis. This is not to say
that there is a problem, merely a concern that needs further investigation.
The calibration of load research data in order to match assigned Utah
Jurisdictional load with the sum of census data plus load research data.
It was decided that the Company would no longer calibrate load research data in
this manner, thus removing some of the concerns that were raised in the last two
rate cases. This agreement only addresses the impact upon load research data
but does not address the jurisdictional question regarding the appropriateness of
the assignment of jurisdiction demand and energy values.
The appropriateness of developing a good sample for the Irrigation Class.
It was decided that the Company should not establish a new sample for Irrigation
Customers. Instead of using load research data, the Irrigation Class should
simply be given the jurisdictional average change in rates.
. The use of the load research data for rate design purposes as well as cost
allocation purposes.
It was decided that load research data could be used to better define cost of
service boundaries within the Residential Class regarding tailblock pricing during
the summer months. More work should be done in this area before specific
recommendations are made.
Description of Load Research Techniques
1 July 2002
Rocky Mountain Power
Exhibit No, 52 page 5 of 19
CASE No, PAC-O7-
Witness; Mark E, Tucker
Load Research Working Group Report to Utah PSG
Techniques used by the Company to develop the load research sample design are
appropriate. The load research protocol is designed to produce a sample that is
accurate within +/- 10 percent on 90 percent of the observations. Although the sample
design is aimed at producing an accurate sample, there are practical problems that
require constant review and vigilance in order to insure that the expected level of
accuracy is achieved. The Working Group addressed three areas where possible
improvements could be made in the load research program:
1. The number of residential load research samples being collected could have
been below an acceptable number of samples necessary to produce the desired
precision and accuracy of the sample. This potential problem has been
corrected with the addition of a number of new residential sample sites during
early 2000.
2. Sample customers are grouped according to size (usage) into what are referred
to as Strata. Weightings are then assigned to the various Strata in order to
reflect the relative percentage of the population as a whole that is represented by
customers within that Strata (usage range). A concern has been raised with
respect to sample migration with sample customers moving from one stratum to
another while the data being collected from that customer continues to be
assigned to the original stratum. It is also recognized that the electricity usage of
the population as a whole varies from month to month. Much of this sample
migration could simply mimic the overall change in usage of the general
population. Since the Company is still gathering data on the migration issue, this
Working Group has not had an opportunity to review the data prior to the
deadline for this report. However, the identification of the concern should help to
insure consideration of the issue in future load research efforts.
3. A concern was also raised regarding how the Company checks the accuracy of
its load research data against the total population billed energy usage.
present, an initial adjustment is made to the load research data if its derived
energy levels differ from the general population by more than +/- 10 percent.
The Company is checking to see if each sample stratum is also found to be
within +/- 10 percent of its respective portion of the general population , however
the Company has stated that the design precision levels are developed for the
whole sample and are not applicable to the individual strata. The identification of
the concern should help to insure that future load research efforts will be more
aware of possible large discrepancies in usage between the various stratum and
the portion of the general population they represent.
Quality of Load Research Data and Calibration Adjustments
In the last two PacifiCorp general rate cases concern has been raised regarding the
impact of calibrations that have been made to the Company s load research data. The
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 6 of 19
CASE No, PAC-O7-
Witness; Mark E. Tucker
specific calibrations of concern are the ones that come about when the summation of
the Company s load research data and the directly measured census data do not equal
the Utah Jurisdictional assigned load or "Jurisdictional Border Load" in any given hour.
The Working Group has generally agreed that anyone of three components (load
research data, census data, and/or Utah Border Load data) could have an error that
impacted these calibration factors.
The Working Group agreed on several points with respect to these calibrations that had
historically been applied to the load research data:
. The general conclusion was that there is something occuring within the Utah
Border Load that is more likely the source of the calibration problem than the
load research data or the census data. The Working Group agreed that the
Company should discontinue the practice of calibrating Utah load research data.
Although the above agreement solves the problem of the large and biased
calibration factors that have been placed upon load research data in recent rate
cases, it does not address the source of these high calibration factors or why
measured/sampled retail loads in Utah (plus expected losses) do not equal the
Utah Border Load. It was concluded that the reason for this discrepency was a
result of the losses associated with wholesale and other system transactions that
get assigned to the retail jurisdictions. Since this is an important issue, but
beyond the scope of this Working Group, it is recommended that these losses be
addressed in another forum.
Use of Load Research Data to Develop Residential Rate Desion
The review of the Company s load research data resulted in an analysis of the usage
characteristics of the sample customers and how that usage fits the definition of the
various stratum boundaries. It was observed that during the summer months
residential customers using over 1,000 kWh per month were more coincident with the
system peak than were smaller residential customers. This suggested that, during the
summer months , generation and transmission costs were higher for the larger
customers and could support an inverted rate block pricing structure. At the same time
it was noted that the larger customers had higher non-coincident peak load factors than
the smaller residential customers. It was recommended that a cost of service study be
prepared for the summer months that separated the residential class into customers
over 1 000 per month and customers using less than 1 000 kWh per month.
A preliminary study was prepared on an annual basis (not just the 4-summer months)
which segregated the residential class between those customers using more than
000 kWh per year and those using fewer than 12 000 kWh per year. On an annual
basis the study results showed that the generation and transmission component cost of
service was higher per kWh for the larger residential customers. However, this
difference was more than offset by a lower cost of service per kWh for the distribution
and retail components. This suggests that, on an annual basis , an inverted rate was
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 7 of 19
CASE No. PAC-O7-
Witness; Mark E, Tucker
not supported. It is important to note that the study did not segregate costs by season.
Without a detailed cost of service analysis it is impossible to determine how significant
the difference in cost of service during the summer months actually is.
While this analysis was discussed , it is agreed by the Working Group that this is a
pricing design issue and not a load research issue.
IrriQation Load Research
From a load research perspective the Irrigation Class has historically been a difficult
group to sample. The Utah Irrigation Class represents only about one percent of the
jurisdiction s total customers and one percent of the jurisdiction s energy requirement.
Compared to its size, however, the Irrigation Class is expensive to sample.
Furthermore , Irrigation Customers can drastically change usage from one year to the
next which could mean that sample meters that are installed one year may not produce
results during the next year, or only during a portion of the irrigation season.
The Company recognizes that its irrigation load research data is stale and some
alternative needs to be found for future rate cases. The Working Group recommends
that the Company not develop a new load research sample for Utah Irrigation
Customers. The Working Group also recommends that whenever rates are changed
for the Utah Jurisdiction as a whole , the Irrigation Customers should get the
jurisdictional average percentage rate change.
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No. 52 page 8 of 19
CASE No. PAC-O7-
Witness; Mark E, Tucker
Description of Load Research Techniques
The most significant demand related costs are production and transmission costs
which are related primarily to each rate schedule s demand at the time of the system
peak (coincident peak demand). Unfortunately, most customers do not have demand
meters. Furthermore, most of the customers that do have demand meters have
demand meters that only register the highest 15-minute demand during the month
(which may not be at the time of the system peak). Generally, only customers with
demands equal to or greater than 1 MW have their loads continuously monitored.
Therefore, coincident peak demands for all rate schedules except the very largest must
be estimated through the use of load research techniques. The Company does this by
placing special load research meters on a random sample of customers from each rate
schedule. Data from these samples is used to estimate the coincident peak demands
for each rate schedule from which the 12 CP is calculated.
The Company s Load Research Department made presentations and answered
questions throughout the course of the Working Group meetings. At the 15 January
2002 meeting, the Company presented an overview of its load research efforts in Utah
and other jurisdictions. This presentation is a good point of reference and is included
as Appendix A of this Report.
The load research data is gathered from stratified random samples. Customers are
grouped by annual energy usage and then a specific number of samples are taken from
each of the stratum. The number of samples taken from each stratum is a function of
the size of the stratum and the variation in customer usage within the stratum. For
example, the Residential Class was divided into four strata along the lines of the
following annual usage ranges:
Lower Upper Weighting Sample
Stratum Usa Usa Factor Points
000 43.
001 000 41.
001 000 13.
001 999 999
The energy consumption data is the only known quantity, and thus , it is the basis for
setting the stratum boundaries. Energy consumption is also used as one check on the
validity of the load research results within each rate schedule. The load research
sample results for each rate schedule are scaled up to the overall population of the rate
schedule. The resulting energy values are then compared to the actual energy
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 9 of 19
CASE No, PAC-O7-
Witness: Mark E. Tucker
readings taken from the rate schedule population as a whole. If the energy levels from
the load research program result in values in any given month that deviate from the
actual measured energy results for a rate schedule by more than +/- 10 percent, then
an adjustment or calibration is made to bring the load research results for that particular
rate schedule in line with the actual results. This first level calibration should not be
confused with the calibration that is made to all load research data for all customer
classes in order to bring the total measured Utah Load in line with the Utah Border
Load data. Generally, such first level calibrations have not been required for the
residential customers or the small commercial customers taking service under Rate
Schedule 23. Occasionally there has been a need to make such an adjm~tment to Rate
Schedule 9, but this adjustment is only made to the sampled group of smaller (under
MW) Schedule 9 customers, which represented only about five percent of the total load
of that schedule.
Although the load research samples are designed to produce results that were accurate
within +/- 10 percent on 90 percent of the observations, there were some practical
problems that may have made this data less accurate than theory would suggest. The
first problem is the number of valid samples actually taken. As pointed out above, the
present design of the residential sample calls for 74 samples to be taken in the first
stratum. Actual sampling data between January 1999 and September 2000 showed
that the number of samples ranged from 50-69 samples. The low number of samples
typical of the sampling in 1999. In early 2000, the residential sample was revised and
new sample customers were added. Since that time , it appears that the number of
Residential Customers being sampled is adequate to meet the study protocol.
A second problem that was addressed is a form of sample migration. Stratum
boundaries have been set up on the basis of annual consumption. For example , the
Residential Stratum 1 Customers are those that have an average monthly usage
between 0 and 500 kWh (annual usage between 0 and 6 000 kWh per year). It was
found that although the appropriate number of customers may have been sampled
within any give stratum certain customers may have used more or less energy than the
range of average usage specified for members of that stratum. In the case of the
Residential Stratum 1 Customers a sample customer may have an average monthly
usage between 0 and 500 kWh , but usage in one or more months may exceed 500
kWh. Thus , during some months this customer would have usage that is similar to that
of a customer in Stratum 2. Likewise, it is possible for a customer from Stratum 2 with
average monthly usage between 501 and 1 000 kWh (annual usage between 6 001
kWh and 12 000 kWh) to occasionally use less than 500 kWh per month --usage similar
to a customer in Stratum 1.
One concern with sample migration is that the data from each sample is weighted by
predetermined values that are based upon annual , not monthly, usage characteristics
of the sample customers as they relate to the usage characteristics of the general
population. If some sample customers are assigned to one stratum, but the usage
characteristics for a given month reflect the usage levels of a different sample stratum
then the weighted sample results may not be reflective of the actual general population
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 10 of 19
CASE No, PAC-07-
Witness; Mark E, Tucker
usage pattern. It was noted that there was generally greater usage by all sample
customers during the summer months, which contributed to this movement of
customers across stratum boundaries. It is possible that this general increase in usage
is reflective of shifts within the general population. The Company maintains that this is
in fact the case. The Working Group has not come to any conclusions regarding the
monthly shifts in usage as they relate to the fixed limits of the stratum boundaries that
are based upon annual consumption.
A related question arose regarding the way the Company checks the accuracy of its
samples each month by comparing the energy usage of the sampled customers
grossed up to the general population , with the actual energy usage of the general
population. As mentioned above, if there is a deviation of greater than +/- 10 percent in
the estimated and sampled energy usage of any given month for a given rate schedule
then an adjustment is made. However, this adjustment is based upon the summation of
all stratum compared to the rate schedule as a whole. Therefore, it is possible that one
or more stratum can be off by more than +/- 10 percent yet the summation of the
stratum are within +/- 10 percent of the general population. As with the sample
migration problem mentioned above , the Working Group has not come to any
conclusions regarding the impact of the accuracy of the sample collection on a stratum-
by-stratum basis.
The Company maintains that seasonal usage fluctuations are present throughout the
entire residential population and that resulting strata migration is accounted for by using
annual energy as the sampling variable. No adjustments should therefore be made to
the stratum level load research estimates.
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page II of 19
CASE No. PAC-07-
Witness; Mark E. Tucker
Quality and Reliability of Load Research Data
As It Relates to Calibration Adjustments
The Company s Load Research Group has, as a matter of routine, calibrated hourly
load research estimates obtained from all non-census rate groups to the hourly Utah
jurisdictional system loads. These calibrations were applied to all load research
estimates in an attempt to true up the load research data to the "actual" system loads
reported for the State of Utah. This methodology was based on the supposition that the
Utah Jurisdictional Loads 1) accurately depict the actual hourly electrical usage for the
State of Utah , and 2) were appropriately comparable to the summed Utah Firm Retail
Class Loads being estimated by the Load Research Group.
Prior to the Pacific Power - Utah Power merger, class load calibration was performed
on all sample load estimates for Utah , Idaho , and Western Wyoming (UP&L) beginning
with the 1983 annual load reports. Post-merger, ongoing load studies in Idaho and
Wyoming were removed and new load studies were conducted on a cycle basis (each
class is monitored for two-years on a five-year rotation). Cycle rotation was
implemented for these states in an effort to reduce costs. Residential and small
commercial and industrial usage patterns in these jurisdictions did not change
materially from one year to the next. Without benefit of ongoing load research sample
data to compare to the measured jurisdictional loads, calibration was discontinued for
Idaho and Wyoming in 1998.
Load research studies for Oregon , Washington , California and Eastern Wyoming are
conducted on a cycle basis and for this reason calibration has not been performed in
these states.
In the most recent PacifiCorp rate cases, concern was raised about the quality and
reliability of the load research data used in the class cost of service studies. These
concerns centered round the calibrations that were applied to the load research data in
order to make the summation of the load research data and the Census data equal to
the measured Utah Border Loads. There were a number of concerns raised with
respect to these calibrations including:
1) In Docket 99-035-10 the calibrations that were used for 10 out of the 12
coincident peaks in the test year were positive, thus adding to the peak load
attributed to these customers;
2) The magnitude of these coincident peak calibrations was large, with five out
of the 12 months having calibrations in excess of a positive nine percent;
3) In Docket 01-035-01 it was demonstrated that the calibrations averaged a
positive seven percent over a two-year period; and
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 12 of 19
CASE No, PAC-O7-
Witness: Mark E. Tucker
4) In Docket 01-035-01 it was demonstrated that there was a definite seasonal
and time-of-day pattern associated with the magnitude of the calibrations.
The cause of the magnitude of the calibrations as well as the seasonality and time-of-
day nature of these calibrations was the focus of one portion of the Working Group
activities. It was recognized that there were at least four factors that contributed to the
magnitude of the calibrations factors on an hourly basis and ultimately the peak
demand usage of each rate schedule. Those four factors are as follows:
Load research uses sampling to define load requirements for the smaller
customers-reflecting roughly 75 percent of jurisdictional load.
Census data from individual large customers that are individually measured
as opposed to sampled-reflecting the remaining 25 percent.
Utah Jurisdictional Border Load-used to define how much energy is
consumed (including any losses that take place) in the State of Utah.
Average losses (developed in 1991) are applied to the load research data.
These losses likely change over time and temperature.
If the summation of the load research data and the census data do not equal the Utah
Jurisdictional Border Load in any given hour, then a calibration has historically been
made to the load research data only, such that the summation of the load research data
and the census data do equal the Border Load. Anyone of these four components
could have an error that resulted in an impact upon these calibration factors.
The review of the calibration data in Docket 01-035-01 was confined to the average
percentage calibration of the load research data for each hour of each month. Under
the Working Group, a closer look was taken at the level of calibrations that took place
during each hour for the months of January and September 2000. It was discovered
that not only was there a time-of-day pattern to the level of the calibrations , but that this
time-of-day pattern was dependent upon the day of the week, with weekends being
distinctively different than weekdays. Appendix B contains a listing of the hourly
percentage calibrations that were encountered for each hour in September 2000 with
Sundays and Holidays" highlighted. The "Average" hourly calibration for the month of
September 2000 is the same as that used in Exhibit CCS- 7.10 page 1 of 3 in Docket
01-035-01 and serves as the basis for the analysis here. The basic findings were:
Under the first eight hours of the day the "Average" calibration of the same
hour in the month, the "Average" calibration is generally over 10 percent.
During the middle of the day the "Average" calibration dips to five percent or
less, while it generally climbs to six percent or greater during the latter part of
the day.
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 13 of 19
CASE No. PAC-07-
Witness; Mark E, Tucker
It was found that the "Sunday/Holiday" calibrations are somewhat higher than
Average" during the first eight hours of the day, significantly higher than the
calibrations during the middle of the day, and moderately higher than the
calibrations during the last eight hours.
. Saturday s calibrations are actually a little less than "Average" during the first
eight hours, more than "Average" but less than Sunday calibrations during the
middle of the day, and unlike either set of values during the last eight hours.
There is a well defined "6 x 16" pattern associated with the calibration data
where the highest calibrations occur during the hours of approximately
midnight to 8:00 a.m. and all day on Sundays and Holidays.
Another observation is that (except for Sundays and Holidays) these
calibrations abruptly go from very high during the first eight hours of the day
to very low calibrations during the next eight hours with virtually no transition.
There appears to be a similar, although less dramatic, jump in the opposite
direction between the hours of 16:00 and 17:00 (4:00 p.m. and 5:00 p.
Up until this point, the calibration problem had only been measured on the basis of the
percentage calibration that was being applied to the load research data. It was
suggested that because the loads vary by hour, it would be of value to also review the
calibration problem on the basis of the actual magnitude of the calibration. Appendix C
lists the actual magnitude of the calibration for each hour of September 2000. Although
this provided a different perspective on the problem, it did not drastically alter the
results. Most noticeably, the major drop in the level of calibrations still occurs at the
8:00 a.m. hour. Sundays still have a high calibration all day long, and calibrations start
a somewhat abrupt increase between the 16:00 and 17:00 hours.
However, the exercise of using actual data as opposed to percentage data brought out
another aspect of the calibration problem. The data used by the Company s Load
Research Department to equate the census and load research data with the Utah
Border Load data includes the use of the peak loss data that has historically been
developed for Utah. The shortcoming with this approach is that peak loss factors are
only appropriate for use during a few hours during the year. Throughout the course of a
day or a month there will be many more hours when the loss factors are closer to the
average loss factors and even less than the average losses. Given the magnitude and
nature of the loss factors, this means that the percentages and the absolute magnitude
of the loss factors listed in Appendix Band C are generally significantly understated.
The Working Group sought to identify the source of the high calibrations that were
being added to the load research data used in the Company s rate cases. Because of
the dramatic (and well-defined) changes in calibrations , it was presumed that the
source of the calibration problem should be detectable by a review of the hourly
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 14 of 19
CASE No. PAC-O7-
Witness: Mark E, Tucker
differences in data around the 8:00 a.m. hour for the load research data , the census
data, and the Utah Border Load data. The hourly load research data and census data
for the month of September 2000 around the hour of 8:00 a.m. was reviewed.
Generally speaking, there were no hourly changes for any rate schedule or census
group data of the magnitude found in the calibration data over this timeframe.
The general conclusion was that there is something occuring within the Utah Border
Load that is more likely the source of the calibration problem than the load research
data or the census data. The Working Group agreed that the Company should
discontinue the practice of calibrating Utah load research data such that the sum of the
load research data and census data equate to the Utah Border Load data for the
following reasons:
1. The calibration process requires uniform derivation and application of the
jurisdictional loads, class load studies, and demand loss factors. Deficiencies in
any of these contributing functions could contribute to inappropriate calibration
results. The current methodology assumes that all calibration differences are
attributable to load study sample error. We no longer believe this assumption to
be reasonable.
2. Compilation of the Utah Class loads is delayed by months while the jurisdictional
loads are prepared. Jurisdictional loads are input into the calibration process.
3. It is questionable that load research sample estimates are improved in the
calibration process , and in fact from a statistical sense , they may be adversely
impacted.
4. Significant resources are required to perform hourly calibration with no apparent
benefit.
Although the above agreement solves the problem of the large calibration factors that
have been placed upon load research data in recent rate cases, it does not address the
source of these high calibration factors or why measured retail loads in Utah plus
expected losses do not equate to the Utah Border Load. It was concluded that the
reason for this discrepancy was the treatment of the losses associated with wholesale
and other system transactions in the development of the Border Loads for all states.
Given the agreement to remove the calibrations from the load research data , it was
concluded that investigation of the impact of this discrepancy between measured Utah
Retail Load and Utah Border Load is outside the scope of this forum. The Working
Group recommends that the Commission establish or identify another forum and direct
the parties to investigate this discrepancy in that forum.
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 15 of 19
CASE No. PAC-E-O7-
Witness; Mark E, Tucker
Use of Load Research Data to Develop Residential Rate Design
When reviewing the residential load research data, an effort was made to determine if a
relationship exists between monthly usage and monthly coincident peak demand. For
purposes of this analysis, all monthly load research data was combined from all stratas
and then ranked by the amount of energy usage. At the upper usage levels (above
000 kWh per month), there was a great deal of overlap during the four summer
months between customers of various stratum with all four stratum having some
customers with usage greater than 1 000 kWh per month.
It was found that there was a decline in the monthly coincident load factor during the
four summer months (June through September) which means that the larger
usagecustomers had usage more coincident with the monthly system coincident peak
than lower usage customers. This indicates that, during the summer, generation and
transmission costs are higher for the larger residential customers than smaller
residential customers. Although an exact line of demarcation was not established , the
decline in monthly coincident load factor was generally believed to occur near 1,000
kWh of usage. A similar relationship between usage level and monthly coincident peak
was not found for the other eight months of the year. The above data suggests that an
inverted block rate starting at approximately 1 000 kWh may be appropriate for the
Residential Class during the summer months. (It is at 400 kWh currently.
A similar review was made of the monthly non-coincident peak data for the Residential
Class. For purposes of this analysis all monthly load research data was combined for
all stratum and then ranked by the amount of energy usage. Unlike the monthly
coincident peak data, it was found that there was an increase in the monthly non-
coincident load factor during the four summer months (June through September) which
means that the larger usage customers used their electricity on a more uniform basis
when compared to the lower usage residential customers.
The conclusion of the Working Group is that this data was significant enough to warrant
further analysis through a cost of service study. It is not only important to identify what
type of customer behavior causes increases in costs , but the actual amount of increase
in costs needs to be quantified as well. Although the load research data serves as the
foundation for much of the data that goes into a cost of service study, it is not a simple
matter to incorporate the above findings into such a study. One way to incorporate the
above data into a cost of service study is to divide the residential customers into two
groups, one that uses over 1 000 kWh during any of the summer months and one that
does not. Under this approach there is a need to review the Company s bill frequency
data and determine how many customers fit this description and how to get the load
research data compiled to properly reflect this bifurcation of the Residential Class.
Further work will need to be done in order to break the cost of service study out into one
more customer category such that the resulting data simply divides the Residential
Class into two groups , but has no impact upon the other rate schedules.
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No. 52 page 16 of 19
CASE No, PAC-O7-O5
Witness: Mark E, Tucker
A preliminary study was prepared which segregated the residential class between those
customers using more than 12 000 kWh per year and those using fewer than 12 000
kWh per year. As suggested in the review of the load research data, the study showed
that the generation and transmission components cost of service were higher, on a
cents per kWh basis, for the larger residential customers. However, this difference was
more than offset by a lower cost of service per kWh for the distribution and retail
components. This suggests that, on an annual basis, an inverted rate was not
supported from a cost of service standpoint.
However, the study did not segregate costs by season. Additional analysis that isolates
the effect of the cost differences to the summer period is needed to determine if an
inverted rate for larger residential customers can be supported during that period.
The above work was completed just prior to the submission of this report to the
Commission and has not been thoroughly reviewed by the Working Group. Although
additional analysis is needed, the Commission should be aware that there is data
available upon which it can assess the price impact of summer usage patterns in the
Utah Jurisdiction. Although this information should not be the sole basis for any
residential rate design decisions, the information should serve the Commission well in
understanding the relationship between certain usage patterns and costs.
The Working Group believes that the residential load research data collected since
early 2000 is of sufficient quality to conduct the above described inverted block pricing
study.
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 17 of 19
CASE No. PAC-E-O7-
Witness: Mark E. Tucker
Irrigation Load Research
From a load research perspective the Irrigation Class has historically been a difficult
group to sample. The Irrigation Class has been a small class within the Utah
Jurisdiction with only about one percent of the jurisdiction s total customers and one
percent of the jurisdiction s energy requirement. Compared to its size, the Irrigation
Class is expensive to sample. The Irrigation Class is highly diversified , and thus
requires more samples per total number of customers in order to get a sample of
desired accuracy and precision. In order to adequately sample the Irrigation Class
100-120 load research meters are required. By comparison , approximately 170 load
research meters are required for the Residential Class that is 30-40 times larger than
the Irrigation Class. Furthermore, Irrigation Customers can drastically change usage
from one year to the next which could mean that sample meters that are installed one
year may not produce results during the next year, or only during a portion of the
irrigation season.
The cost of gathering good load research data for Irrigation Customers has led to the
use of stale load research data in recent rate cases. The Company s cost of service
studies have included values for irrigation loads that are taken from data gathered in
the 1991-1993 timeframe and then massaged in an attempt to simulate test year
results. The resulting cost assignments to the Irrigation Class have been the source of
a great deal of contention during these cases. The Company recognizes that its
historical irrigation load research data is stale and some alternative needs to be found
for future rate cases.
Two alternatives were reviewed. The first alternative was to initiate a new load
research sample for irrigators in Utah. The cost of this alternative was explored and it
was decided that it was not worth the price-especially considering the fact that
Irrigation Customers would continue to change watering requirements and thus usage
from year to year.
The second alternative addressed by the Working Group was proposing a stipulation
that would allow the Company to avoid designing and gathering a new load research
sample for the Irrigation Customers. As a part of this stipulation , it was also agreed that
whenever rates are changed for the Utah Jurisdiction as a whole , that the Irrigation
Customers get the jurisdictional average rate change.
The specific working of the stipulation is as follows:
For at least the last decade , the Irrigation Class comprises less than one
percent of the total kWh sales in Utah. Due to the relatively small size of
the Irrigation Class in Utah, and the potentially high cost of implementing
new load research samples to improve load research studies, the parties
agree that new load research samples are not necessary for the
Load Research Working Group Report to Utah PSG
Rocky Mountain Power
Exhibit No, 52 page 18 of 19
CASE No. PAC-07-
Witness; Mark E. Tucker
foreseeable future. As a result, the parties also agree that in subsequent
cases where rates are changed and where new load research studies have
not been employed for the Irrigation Class, that the proposed rate spread
for Irrigation Customers will be equal to the overall average jurisdictional
percentage change.
It is the intent of all parties that have participated in this Working Group that at the next
appropriate opportunity, the above language will be presented to the Commission for its
consideration with respect to how the revenue requirement for the Irrigation Class
should be calculated in the future without new load research data.
1 July 2002
Rocky Mountain Power
Exhibit No, 52 page 19 of 19
CASE No, PAC-07-
Witness: Mark E, Tucker
Load Research Working Group Report to Utah PSG
Appendix
PacifiCorp s Overview Presentation of its Load Research Program
September 2000 Hourly Percentage Calibrations
September 2000 Hourly MWH Calibrations
Cost of Service by Rate Schedule
""',
,", A '- 1\
2fifilOCT 26 Ar1 10: 50 Case No. PAC-07-
Exhibit No. 53
lDi\HO PUBLIC . Witness: Mark E. Tucker
UTILITIES COMMISSIOr
BEFORE THE IDAHO PUBLIC UTILITIES COMMISSION
ROCKY MOUNTAIN POWER
Exhibit Accompanying Rebuttal Testimony of Mark E. Tucker
Alternate Allocation of Rate Mitigation Cap
October 2007
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