20230301Eldred Revised Direct with Exhibits.pdf

BEFORE THE

IDAHO PUBLIC UTILITIES COMMISSION

IN THE MATTER OF THE APPLICATION
OF VEOLIA WATER IDAHO, INC. FOR A
GENERAL RATE CASE

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CASE NO. VEO-W-22-02

REVISED DIRECT TESTIMONY OF MICHAEL ELDRED

IDAHO PUBLIC UTILITIES COMMISSION

MARCH 1, 2023

RECEIVED
2023 March 1, PM 3:48
IDAHO PUBLIC
UTILITIES COMMISSION

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 1
03/1/23 STAFF
Q. Please state your name and business address for
the record.
A. My name is Michael Eldred. My business address
is 11331 W. Chinden Blvd., Building 8, Suite 201-A, Boise,
Idaho 83720.
Q. By whom are you employed and in what capacity?
A. I am employed by the Idaho Public Utilities
Commission (“Commission”) as a Utilities Analyst in the
Utilities Division.
Q. Please describe your work experience and
educational background?
A. Please see Exhibit No. 122 that provides a
summary of my work experience and education background.
Q. What is the purpose of your testimony in this
proceeding?
A. The purpose of my testimony is to address the
Company’s Test Year Revenue at Present Rates and normalized
consumption adjustments used to determine (1) the baseline
for determining the increase (or decrease) in revenue the
Company will earn as result of this case, and (2) the
Company’s Cost of Service Study (“COSS”) used to inform the
spread of the Revenue Requirement across the different

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 2
03/1/23 STAFF
classes.
I also provide an assessment of the Load Study
conducted in response to Commission Order No. 35030 that
was intended to validate whether the Company’s customer
classes are appropriate to ensure customers are being
charged based on the costs that they cause based on their
demand and usage patterns.
For purposes of my testimony, the terms “usage”
and “consumption” can be used interchangeably and refer to
the amount of water purchased by customers from the
Company’s system.
Test Year Revenue and Weather Normalized Consumption
Q. Please summarize your findings as a result of
your review of the Company’s Test Year Revenue at Present
Rates and Weather Normalized Test Year Consumption.
A. I generally support the Company’s methods for
determining the Test Year Revenue at Present Rates filed in
the Company’s Application; however, Staff is proposing to
use a 2022 Test Year, January 1, 2022, through December 31,
2022, without pro forma adjustments, instead of the
Company’s proposed Test Year of July 1, 2021, through June
30, 2022, with pro forma adjustments through March 31,

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 3
03/1/23 STAFF
2023. The rationale for the Test Year change is described
in Staff witness English’s testimony.
The change in the Test Year has the following
effects related to my testimony:
1. Test Year Revenue at Present Rates should be
increased $738,348 from $51,717,859 to
$52,456,207, which is reflected as adjustment No.
4 in Revised Exhibit No. 130 of Staff witness
Culbertson’s testimony;
2. Total water consumption for the Test Year should
be reduced from 857,424 one hundred cubic feet
(“CCF”) as proposed by the Company to 823,098
CCF; and
3. A downward adjustment of $8,905 should be applied
to power and chemical expense as a result of the
reduction in Test Year consumption compared to
the Company’s Application as reflected as
adjustment No. 28 in Revised Exhibit No. 130 of
Staff witness Culbertson’s testimony.

Q. Does this testimony replace your initial pre-
filed testimony?

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 4
03/1/23 STAFF
A. Yes, this updated testimony replaces my initial
pre-filed testimony that was filed on February 15, 2023.
Q. Why did your initial testimony need to be
updated?
A. My initial testimony provided estimates for the
Revenue at Present Rates. Staff did not receive a full
response from the Company to Staff Production Request
(“PR”) No. 163 before my pre-filed testimony was due on
February 15, 2023. The Company did provide an Interim
Response to PR No. 163 that provided enough information to
determine estimates for Staff’s Revenue at Present Rates in
my initial testimony for Staff’s 2022 Test Year. On
February 21, 2023, the Company provided the Updated
Response to PR No. 163 with all the information I needed to
perform a full analysis and to update my testimony and
exhibits associated with the Test Year Revenue and Weather
Normalized Consumption Section of my initial testimony.
This updated testimony replaces my initial pre-filed
testimony.
Q. What exhibit supports your testimony on Staff’s
recommendation for Revenue at Present Rates?
A. I have included Revised Exhibit No. 123 with 4

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 5
03/1/23 STAFF
schedules to support my testimony. Schedule 1 is a summary
showing the overall total differences between Staff’s final
recommended Total Test Year Revenue at Present Rates and
the Company’s Total Test Year Revenue at Present Rates
included in its Application and in Updated Response to PR
No. 163. Schedule 2 is the Company’s Total Test Year
Revenue at Present Rates included in its Application using
the Company’s proposed Test Year with pro forma
adjustments. Schedule 3 is the Total Test Year Revenue at
Present Rates provided in Updated Response to PR No. 163
using Staff’s 2022 Test Year without pro forma adjustments.
Schedule 4 is Staff’s final recommended Total Test Year
Revenue at Present Rates using Staff’s 2022 Test Year
without pro forma adjustments.
Q. Please describe how the Company developed its
final Test Year Revenue under Present Rates as contained in
the Application.
A. As discussed earlier, the Company’s proposed
Total Test Year Revenue at Present Rates is summarized in
Company Exhibit 5, Schedule 1, in the Company’s
Application, which I have included as Revised Exhibit No.
123, Schedule 2 of my testimony. It reflects a total

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 6
03/1/23 STAFF
revenue of $51,717,859 (Column 11), which is comprised of
$50,866,102 of Adjusted Historic Test Year Book Revenue
(column 4), and five adjustments increasing the Test Year
revenue by a total of $851,757 (Columns 6-10). To
determine the adjustments, the Company was required to
perform a Bill Analysis of the Test Year revenue, which
breaks down the amount of revenue earned through each rate
component on customer bills for each customer class. The
total of this breakdown (Column 5) is shown to reconcile
with the Adjusted Historic Test Year Book Revenue (Column
4), validating the Bill Analysis. The adjustments to the
Bill Analysis Revenues Historic Test Year Rates (Column 5)
broken out in Columns 6 through 10 include the following:
1. Adjustment R1 - Annualization of Historic Test
Year Growth for $246,816 (Column 6);
2. Adjustment R2 – Customer Growth from 7/1/21-
3/31/22 for $273,782 (Column 7);1
3. Adjustment R3 - Weather Usage Adjustment for
$(2,691,767) (Column 8);
4. Adjustment R4 Eagle Historic Test Year for

1 Staff verified the dates on this column are mis-labeled as
7/1/20 - 3/31/21 and should have contained date range
7/1/21 - 3/31/22.

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 7
03/1/23 STAFF
$661,051 (Column 9); and
5. Normalization of Phase I Rates for $2,343,875
(Column 10).
Q. Can you provide an overview of Staff’s proposed
changes to the Company’s Test Year Revenue at Present
Rates?
A. I have included a summary of Staff’s final Test
Year Revenue at Present Rates, as shown in Revised Exhibit
No. 123, Schedule 4 using the same format used by the
Company. As mentioned earlier in my testimony, Staff’s
proposal to the Test Year Revenue under Present Rates is
driven by changing to a 2022 Test Year.
Q. Did the Company provide a Test Year Revenue under
Present Rates reflecting Staff’s 2022 Test Year?
A. Yes, the Company provided a Test Year Revenue
under Present Rates reflecting Staff’s 2022 Test Year
through the Company’s Updated Response to Staff PR No. 163.
I have included the Company’s written response to PR No.
163 as Revised Exhibit No. 125 of my testimony. The Test
Year Revenue under Present Rates from the Company’s Updated
Response to PR No. 163 is provided as Revised Exhibit No.
123, Schedule 3. I used the Company’s Updated Response to

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 8
03/1/23 STAFF
PR No. 163 as the starting point for Staff’s final Test
Year Revenue at Present Rates, as shown in Revised Exhibit
No. 123, Schedule 4.
Q. Please describe the Book Values (Columns 2-4) in
Staff’s proposal as shown in Revised Exhibit No. 123,
Schedule 4 and how these values were determined.
A. The Booked Values in columns 2 through 4 show
actual booked values with removal of unbilled/surcharge
amounts for Staff’s 2022 Test Year. These values were
obtained through the Company’s Updated Response to Staff PR
No. 163 and match the values seen in Revised Exhibit No.
123, Schedule 3 with the exception of the Meter Reading
Error Rebills line item.
Q. Please explain the Meter Reading Error Rebills
line item and why it is necessary.
A. The Meter Reading Error Rebills line item
represents rebilled revenue that was not included in the
2022 Test Year Booked Values. The value in this line item
is related to rebilling that occurred after the 2022 test
year but is a result of inaccurate meter readings that
occurred from July 2022 through January 2023. The $48,606
value in this line item represents rebills that occur after

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 9
03/1/23 STAFF
the December 31, 2022, cut of date of Staff’s Test Year.
This value was obtained from the Company’s Updated Response
to PR No. 163. This line item is necessary because this
revenue would have been received during the 2022 test year
had the meter reading issue not occurred. Additional
information on the meter reading issue is provided in Staff
Revised Exhibit No. 125.
Q. Please explain what the Bill Analysis Revenues in
Column 5 of Staff’s proposal represent and how the values
were determined.
A. The Bill Analysis Revenues represent consumption
analysis and billing determinants at present rates for
Staff’s Test Year. These values were obtained through the
Company’s Updated Response to Staff PR No. 163 and match
the values seen in Revised Exhibit No. 123, Schedule 3
except for the Meter Reading Error Rebills line item. The
Rebills line item is necessary for the same reasons as
explained earlier and make the Bill Analysis Revenue
reconcile with the Adjusted Historic Test Year Book Revenue
shown in Column 4.
Q. Please explain what the Adjustment R1 -
Annualization of Historic Test Year Growth (Column 6)

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 10
03/1/23 STAFF
represents and how your values were determined.
A. The Company’s R1 adjustment adjusts for growth of
the number of customers during the Test Year. The values
for my R1 adjustment were obtained through the Company’s
Updated Response to Staff PR No. 163 and match the values
seen in Revised Exhibit No. 123, Schedule 3. I reviewed
the Company’s R1 adjustment provided in the Updated
Response to PR No. 163 and agree with the final adjustment
values. I have included the billing determinant
calculations based on Staff’s 2022 Test Year for the R1
adjustment in Revised Exhibit No. 126. The Exhibit follows
the same format as Company Exhibit 5, Schedule 4 VWID, and
Schedule 4 Eagle Worksheets.
Q. Please explain what the Adjustment R2 – Customer
Growth from 7/1/22-3/31/23 (Column 7) represents and how
your values were determined.
A. The Company’s R2 adjustment adjusts customer
growth for its pro forma period from July 1, 2022, through
March 31, 2023. However, under Staff’s proposal, the R2
adjustment is not required. Since Staff is using a 2022
Test Year without a pro forma period, an adjustment for pro
forma period customer growth is not needed. The amount of

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 11
03/1/23 STAFF
customer growth that occurred from July 1, 2022, through
December 31, 2022, the end of Staff’s Test Year, is
incorporated in Staff’s R1 adjustment, as described above.
Q. Please explain what the Adjustment R3 - Weather
Usage Adjustment (Column 8) represents and how your values
were determined.
A. The R3 adjustment determines how much the 2022
Test Year Revenue needs to be adjusted so that the Revenue
at Present Rates represents the amount of Revenue the
Company would have earned if the Test Year experienced a
normal consumption and weather year. To accomplish this, I
ran statistical regression analyses using 31 years of
available historical consumption and weather data provided
by the Company to determine the normalized Use per Customer
(“UPC”) for Residential and Commercial customers for the
2022 Test Year. The difference between the normalized UPCs
for the 2022 Test Year and actual UPCs for the 2022 Test
Year were then multiplied by the number of actual
Residential and Commercial customers at the end of the 2022
Test Year to determine the total usage adjustment for the
two classes. Revised Exhibit No. 126. Using my
recommended normalized UPC adjustment of -7.51 CCF for

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 12
03/1/23 STAFF
Residential customers and -21.57 CCF for Commercial
customers, I estimated the total R3 Weather Usage
Adjustment to be $(1,664,176) using the allocation factors
from the Company’s Bill Analysis provided in the Company’s
Updated Response to Staff PR No. 163.
Q. Please explain how you developed the recommended
normalized UPCs for the 2022 Test Year.
A. To determine the normalized UPCs for the 2022
Test Year, I first compared the Company’s normalization
regression method to my own regression methods for both
Residential and Commercial customers. I used historical
actual consumption data included in the Company’s
Application as well as data provided through the Company’s
Updated Response to Staff PR No. 163 so that I had actual
data throughout the 2022 Test Year. My method summed the
results of 12 monthly models to determine the normalized
annual UPCs instead of using a single annual model used by
the Company. I determined that the Company’s regression
modeling method using the 2022 Test Year resulted in
normalized UPC amounts that were within the standard error
of the normalized UPCs that I determined through my own
models. Based on this finding, I utilized the Company’s

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 13
03/1/23 STAFF
modeling method with a couple of exceptions.
Q. Please explain your exceptions.
A. There were two things I did differently. First,
I used 31 years of data, from 1992 through 2022, instead of
30 years used by the Company, since it was available. The
additional data provided an additional degree of freedom
which generally reduces the amount of error in regression
estimates.
Second, the Company’s regression model in its
Application only included actual data through 2021.
Because the Company’s test year went from July 1, 2021,
through June 30, 2022, the Company was effectively making
predictions 6 months past its actual data set. Using the
Company’s method on Staff’s test year would have resulted
in predicting 12 months past the actual data set. Most
introductory statistics texts warn against extrapolation,
that is, using regression to make predictions beyond the
range of the original data set.2 Given that the actual data

2 See, for example, 1. Pennsylvania State University’s
Department of Statistics course notes for STAT 100:
Statistical Concepts and Reasoning.
https://online.stat.psu.edu/stat100/lesson/5/5.5, 2.
University of West Georgia’s Linear Regression Notes based
on Chapter 5 of The Basic Practice of Statistics (6th ed.).
https://www.westga.edu/academics/research/vrc/assets/docs/l

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 14
03/1/23 STAFF
was available for the Company’s proposed test year as well
as for Staff’s 2022 Test Year, there is no reason not to
include the data in the regression model, thus eliminating
this as a source of error. However, I included actual data
from 1992 through the 2022 Test Year in the regression
model, preventing predictions outside the actual data set
eliminating this as a source of error.
In the Company’s Updated Response to PR No. 163,
they included actual data from 1993 through 2022 in their
regression model but predicted normal consumption for the
year 2023. This approach continues to extrapolate outside
the actual data set and uses a year that does not match
Staff’s test year. For these reasons, I did not use the
Company’s values from the Updated Response to PR No. 163.
Q. What inputs and historic data did you and the
Company use in the regression models?
A. Both the Company and I performed our regression
analysis utilizing actual customer usage, calendar year,
and the Palmer Z index as inputs. Michaelson Direct at 6.

inear_regression_notes.pdf. 3. “Making Predictions with
Regression Analysis”, Statistics By Jim.
https://statisticsbyjim.com/regression/predictions-
regression/.

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 15
03/1/23 STAFF
The Palmer-Z index from the National Oceanographic and
Atmospheric Administration (“NOAA”) reflects weather
conditions that affect water consumption due to irrigation.
The index estimates the moisture content of soil during a
specified time period and geographic locale relative to the
long-term average for that same period and locale. It
incorporates the cumulative effects of temperature,
humidity, precipitation, evapotranspiration, and soil
conditions into a single number, serving as a weather
variable that drives water consumption. Positive values
indicate wetter-than-normal conditions; negative values
indicate drier-than-normal conditions. The Company uses a
7-month Palmer Z index, which is a single composite value
for those months when the Company determined that customer
irrigation is most likely, from April through October.
Q. Are there any improvements that you believe
should be incorporated in the Company’s models in its next
general rate case?
A. There are two improvements. First, I advocate
either creating 12 monthly models similar to the models I
developed and used to compare against the Company’s annual
model, or include monthly data and variables in a single

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 16
03/1/23 STAFF
regression model. I believe the added resolution of
monthly data and variables is better to determine the
effects of weather to the amount of water consumption
because it more accurately matches the weather conditions
in each month to the amount of water consumed in each month
over the dataset timeframe. This is especially important
because weather conditions can vary widely during the
course of any given year.
Second, I suggest normalizing for economic
conditions such as wages, employment rate, and some measure
of buying power due to inflation. In any regression model,
it is important to identify the statistically significant
causal factors that contribute to customer water
consumption as the independent variable. Doing so better
isolates the effects of weather from other causal factors
and improves the overall accuracy of the model.
I recommend that the Company, Staff, and other
interested parties meet prior to the next general rate case
to discuss the importance and methods of making these
changes in the Company’s regression methodology.
Q. Please explain what the Adjustment R4 - Eagle
Historic Test Year (Column 9) represents and how your

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 17
03/1/23 STAFF
values were determined.
A. The Company’s R4 adjustment makes an adjustment
to include revenue for Eagle Water legacy customers as if
the Company was providing service from July 1, 2021,
through December 31, 2021, even though the Company did not
provide service to Eagle Water customers until January 1,
2022. This adjustment is required using the Company’s July
1, 2021, through June 30, 2022, test year to ensure the
correct revenue baseline. However, due to Eagle Water
customers being included in the Company’s system for all of
Staff’s 2022 Test Year, no R4 adjustment is required.
Q. Did you propose an adjustment to the Company’s
proposed revenue requirement to reflect the reduced
consumption predicted by your consumption adjustments?
A. Yes. I proposed an adjustment to the Company’s
power and chemicals expenses since these expenses vary in
proportion to water consumption. Because total consumption
changed using a 2022 Test Year as compared to consumption
in the Company’s Application, Staff has included an
adjustment of $(8,905) in power and chemical expense as
reflected in Staff’s adjustment No. 28 in Revised Exhibit
No. 130 of Staff witness Culbertson’s testimony. I used

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 18
03/1/23 STAFF
the same calculation method the Company used to make their
own adjustment after normalizing consumption for their
proposed Test Year as detailed in Company witness Cary’s
Adjustment No. 29.
Q. Please explain what the Normalization of Phase 1
Rates (Column 10) represents and how your values were
determined.
A. The purpose of the Normalization of Phase I Rates
adjusts the Test Year revenue to account for two things:
(1) a rate change for Company and non-legacy Eagle Water
customers that occurred during the Test Year; and (2) to
adjust Test Year revenue for Eagle Water legacy customer
rates that went into effect on January 1, 2023. This
adjustment is still needed for Staff’s 2022 Test Year. The
values for my Normalization of Phase 1 Rates were obtained
through the Company’s Updated Response to Staff PR No. 163
and match the values seen in Revised Exhibit No. 123,
Schedule 3. I reviewed the Company’s Normalization of
Phase 1 Rates adjustment provided in the Updated Response
to PR No. 163 and agree with the final adjustment values.
Q. Please summarize your recommendations related to
the Test Year Revenue at Present Rates and Weather

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 19
03/1/23 STAFF
Normalized Test Year consumption.
A. First, I recommend the Commission approve my
proposed Test Year Revenue at Present Rates and
corresponding adjustments as shown in Revised Exhibit No.
123, Schedule 2. Second, I recommend an adjustment of
$(8,905) to power and chemical expense as a result of the
change in Test Year consumption compared to the Company’s
Application. Finally, I recommend that the Company, Staff,
and other interested parties meet to discuss and agree on
improvements to the weather normalization regression
methodology before the next general rate case.
THE COMPANY’S COST-OF-SERVICE STUDY AND LOAD STUDY
Q. What is the purpose of a COSS?
A. A COSS allocates the Company’s revenue
requirement to the Company’s rate classes in accordance
with the principle of cost causation. The cost causation
principle states that costs should be borne by the class
that causes them to be incurred. Costs incurred in the
service of a single class, or its individual members,
should be directly assigned to that class; however, because
many of the Company's costs are incurred serving multiple
classes, a COSS is necessary to allocate costs that are not

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 20
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directly assigned.
Q. Is the formation of customer classes based on
principles of cost causation widely used in utility
regulation?
A. Yes. It is a bedrock principle of utility cost-
of-service rate making. One example is described in the
Public Utility Regulatory Policy Act of 1978 under Title I,
Subtitle B, section 111(d)(1):

COST OP SERVICE.—In undertaking the consideration
and making the determination under section 111
with respect to the standard concerning cost of
service established by section 111(d)(1), the
costs of providing electric service to each class
of electric consumers shall, to the maximum
extent practicable, be determined on the basis of
methods prescribed by the State regulatory
authority (in the case of a State regulated
electric utility) or by the electric utility (in
the case of a nonregulated electric utility).
Such methods shall to the maximum extent
practicable—
(1) permit identification of differences in cost-
incurrence, for each such class of electric
consumers, attributable to daily and seasonal time of
use of service and
(2) permit identification of differences in cost-
incurrence attributable to differences in customer
demand, and energy components of cost. In prescribing
such methods, such State regulatory authority or
nonregulated electric utility shall take into account
the extent to which total costs to an electric
utility are likely to change if—
(A) additional capacity is added to meet peak
demand relative to base demand; and
(B) additional kilowatt-hours of electric energy

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 21
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are delivered to electric consumers.

Q. Do the classes used in the Company's COSS
correspond to existing rate schedules?
A. No. The Company's COSS allocated costs to four
hypothetical rate classes: Residential, Commercial, Public
Authority, and Private Fire. None of these classes
corresponds to an existing rate schedule.
Customers in the study's Residential, Commercial,
and Public Authority classifications all take service under
Schedule 1, General Metered Service. The study's Private
Fire classification corresponds to two different Schedules:
(1) Schedule 3, Private Fire Sprinkling Service, and (2)
Schedule 4, Private Fire Hydrant service, neither of which
are subject to a volumetric charge.
Q. What is a load study, and why is it a necessary
component of a COSS.
A. Because Company infrastructure and equipment must
be sized to meet the peak load that will be placed on it,
peak load is an important cost driver. A load study should
identify appropriate classes based on differences of how
each class uses the system during peaking events. This
information is then used to develop allocators of cost used

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 22
03/1/23 STAFF
in the COSS.
Q. Did the load study performed by the Company
verify the hypothetical rate classes as the appropriate
classes based on cost causation principles?
A. No, the load study assumed the hypothetical rate
classes are the appropriate classes. The load study did
not perform a robust analysis to verify that the
hypothetical classes or any other potential classes are the
appropriate classes. The load study needed to identify
potential customer classes based on cost causation
principles before collecting data on these potential
classes to make meaningful comparisons between the classes.
Q. Was the Company aware of these needs prior to the
load study being conducted?
A. Yes. The purpose of determining appropriate
classes was identified in the Stipulation authorized in
Case No. SUZ-W-20-02 through Commission Order No. 35030.
As a result of the Order, Staff and other parties met with
the Company about the load study prior to it being
conducted.3 During the meetings, Staff and other parties
emphasized the need to identify potential classes and how

3 Meetings with the Company occurred on 5/16/22 and 6/6/22.

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 23
03/1/23 STAFF
to design a sampling plan so that the data could be
collected to identify what could be appropriate classes
based on the costs they cause on the Company’s system.
Q. What is your position on the Company’s load study
and its usefulness in the COSS?
A. I do not believe the load study was performed in
a manner that makes it used and useful to inform the COSS.
To make it useful, the load study should have identified
the appropriate classes based on data collected during the
load study. Because the load study did not identify
potential classes prior to data collection, differences in
demand and consumption patterns of potential customer
classes could not be determined. As a result, the values
used from the load study and the results of the COSS are
not useful.
Q. What factors should be considered when
determining the data that needs to be collected for the
load study?
A. Ordinarily, load studies are structured around
existing classes; however, as discussed earlier, the
Company’s current rate schedules do not represent the
hypothetical customer classes used in the COSS. It was

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 24
03/1/23 STAFF
therefore necessary to design the load study so that it can
be used to inform the formation and/or validation of
classes.
The Company's current division of its consumptive
customers into Residential, Public Authority, and
Commercial classifications assumes that the customers in
each of these divisions have similar consumptive patterns.
However, this is unlikely true. For example, Residential
customers who live in single family dwellings with yards
and lawns will consume much more water in the summer than
apartment dwellers.
Rather than using the Company's Residential,
Public Authority, and Commercial classifications as the
basis for the load study, the study should have been
conducted using groupings based on meter size, whether
customers irrigate their property with Company water during
the summer months, single family and several different
versions of multi-family housing, lot sizes, types of
processes and equipment used by commercial and industrial
customers, etc. Many of these causal factors that can
influence different usage patterns are listed in the
Seventh Edition of “Principles of Water Rates, Fees, and

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 25
03/1/23 STAFF
Charges,” published by the American Water Works Association
included as Exhibit No. 127.
If the load study collected the data based on
groupings determined by causal factors common within the
Company’s service territory, differences in demand and
usage patterns between groups could be determined,
indicating the need for different customer classes.
The Company’s AMI meters allow the collection of
useful data to help in the determination of customer
classes; however, the implementation of AMI meters across
the Company’s service territory was incomplete. To ensure
sufficient sample size of each potential class that is
representative of the population of customers in the
Company’s service territory, the Company’s rollout of AMI
meters across their service territory could have been
altered to collect the necessary data. However, this would
have required the identification of potential customer
classes needing the additional meters to get a
representative sample.
Q. Briefly summarize the method used to determine
the allocation factors used in the Company’s COSS.
A. The Company used a similar method and allocation

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 26
03/1/23 STAFF
factors that were used in prior rate cases (UWI-W-11-02 and
SUZ-W-20-02).
Q. Do you have other concerns with the Company’s
COSS?
A. Yes, I have two concerns. First, rather than
directly assigning costs to customer classes, the Company
allocated nearly all costs using factors derived in the
2011 rate case, Case No. UWI-W-11-02.
The purpose of a COSS is to allocate the
Company's revenue requirement in accordance with the
principles of cost causation: that is, the class that
caused a cost to be incurred should pay for the cost. When
the customer groups who cause a cost can be clearly
identified, then those costs should be directly assigned to
that customer's class. For example, instead of directly
assigning the costs of meters and meter installations, the
Company allocated these costs based on 5/8" meter
equivalents.
The second concern relates to the Company’s
change in fire demand in the COSS. In the COSS, the
Company changed an assumption for total fire demand from a
single long duration fire to three shorter duration fires

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 27
03/1/23 STAFF
without providing the proper justification for the change.
The result of this change shows fire protection customers
should receive a decrease in rates based of the COSS. In
the Application, the Company proposed private fire receive
no increase and all other customers receive a uniform
increase.
Staff requested justification for the fire demand
change in Staff PR No. 157. Exhibit No. 128. The
Company’s response was not based on any credible evidence
to support the time and demand of the three-fire
assumption. Due to lack of justification for the
assumption change in fire demand and the other issues with
the COSS, I do not agree with the Company’s proposal of no
increase for the private fire rates. I believe the private
fire class should receive a uniform increase like all other
classes.
Q. What are your recommendations to the Commission
regarding cost-of-service?
A. I have four recommendations based on my review.
First, I recommend that the Company use a uniform
percentage increase across all rate components and customer
classes. Without the establishment of consumptive classes

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 28
03/1/23 STAFF
and a valid COSS study, it is impossible to fairly allocate
the increase based on traditional cost causation
principles.
Second, I recommend that the Commission disallow
the COSS and load study expense included in the rate case
because the load study and COSS was not performed in a
manner that makes it useful for the purpose of determining
rates in the rate case. This is a negative adjustment of
$40,817 to the Company’s revenue requirement reflected as
adjustment No. 24, Column 4, in Exhibit No. 130 of Staff
witness Culbertson’s testimony.
Third, I recommend the Commission order the
Company to conduct a new load study and COSS by the next
rate case. The load study and the COSS should be conducted
to determine the need for appropriate customer classes that
are based on traditional regulatory principles of cost
causation as outlined in my testimony. Specific to the
load study, it should be designed to collect demand and
usage pattern data that is representative of potential
consumptive customer classes.
Finally, I recommend that the Commission order
the Company to conduct a workshop with Staff and interested

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CASE NO. VEO-W-22-02 ELDRED, M. (Di) 29
03/1/23 STAFF
parties to determine how the study should be conducted with
the objective that the study meet principles of cost
causation as outlined in my testimony prior to the load
study being conducted.
Q. Does this conclude your testimony in this
proceeding?
A. Yes, it does.
Professional Qualifications Of
Michael Eldred Utilities Analyst II -Engineering
Idaho Public Utilities Commission
EDUCATION
Mr. Eldred graduated with honors from Boise State
University with a bachelor's degree in Mechanical Engineering in
2014 and a master's degree in Business Administration in 2016.
In addition to his formal education, he has attended the
Institute of Public Utilities Annual Regulatory Studies Program
at Michigan State University, attended Michigan State
University's NARUC Utility Rate School, and EUCI Cost of Service
and Rate Design Courses.
BUSINESS EXPERIENCE
Mr. Eldred has worked with the Commission as a Utilities
Analyst since 2017. He has reviewed and provided
recommendations to the Commission in a wide variety of cases due
to his extensive knowledge, skills, and abilities. Some
examples of cases he has processed include: (1) reviewing and
providing recommendations on cost of service studies,
consumption normalization, and rate design proposals in general
rate cases; (2) conducting analyses and providing
Revised Exhibit No. 122 Case No. VEO-W-22-02M. Eldred, Staff
03/01123 Page J of 2
recommendations on electricity and natural gas prices in general
rate cases; (3) conducting prudence reviews and providing
recommendations on capital investments in general rate cases and
Certificate for Public Convenience and Necessity cases; (4)
providing technical advice on integrated resource plans for
various utilities; and (5) reviewing and providing
recommendations on utilities cost recovery mechanisms.
Revised Exhibit No. 122 Case No. VEO-W-22-02 M. Eldred, Staff
03101/23 Page 2 of 2
Name of Test Year Revenues
at Present Rates Total
Revenues
Historic Test
Year Rates
12/31/2022
Removal of
Unbilled,
Surcharges &
Misc
Adjusted
Historic Test
Year Book
Revenue
Revenues
Historic Test
Year Rates
(Schedule 3)
Adjustment 1
Annualization
Year Growth
Customer
Growth from
1/1/23 -
3/31/23
weather usage
adjustment
Eagle Historic
Test Year
Normalization
Normalization
of Phase 1
Rates
Revenue
Present Rates
(1)(2)(3) (4) = (2) + (3) (5)(6)(7)(8)(9)(10)+ (10)
Company's Application Total
Company's PR 163 Total
Staff's Final Total
Staff's Final Total
Company's Application Total
Difference
Staff's Final Total
Company's PR 163 Total
Difference
SUMMARY TABLE OF TEST YEAR REVENUES UNDER PRESENT RATES
Revised Exhibit No. 123
Schedule No. 1
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 1 of 1
Customer Classification
Revenues
Historic Test
Year Rates
6/30/2022
Removal of
Unbilled,
Surcharges &
Misc
Adjusted
Historic Test
Year Book
Revenue
Revenues
Historic Test
Year Rates
(Schedule 3)
Adjustment 1
Annualization
of Historic Test
Year Growth
Customer
Growth from
7/1/20 -
3/31/21
Adjustment R3
weather usage
adjustment
Adjustment R4
Eagle Historic
Test Year
Normalization
Normalization
of Phase 1
Rates
Total Test Year
Revenue
Present Rates
(1)(2)(3) (4) = (2) + (3) (5)(6)(7)(8)(9)(10)
+ (7) + (8) + (9)
+ (10)
SUMMARY OF HISTORIC TEST YEAR REVENUES UNDER PRESENT RATES AND TEST YEAR REVENUES UNDER PRESENT RATES
FOR THE TEST YEAR ENDED MARCH 31, 2023
Revised Exhibit No. 123 Schedule No. 2
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 1 of 1
Customer Classification
Revenues
Historic Test
Year Rates
12/31/2022
Removal of
Unbilled,
Surcharges &
Misc
Adjusted
Historic Test
Year Book
Revenue
Revenues
Historic Test
Year Rates
(Schedule 3)
Adjustment 1
Annualization
Year Growth
Customer
Growth from
1/1/23 -
3/31/23
weather usage
adjustment
Eagle Historic
Test Year
Normalization
Normalization
of Phase 1
Rates
Revenue
Present Rates
(1)(2)(3) (4) = (2) + (3) (5)(6)(7)(8)(9)(10)+ (10)
SUMMARY OF HISTORIC TEST YEAR REVENUES UNDER PRESENT RATES AND TEST YEAR REVENUES UNDER PRESENT RATES
FOR THE TEST YEAR ENDED MARCH 31, 2023
Revised Exhibit No. 123 Schedule No. 3
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 1 of 1
Customer Classification
Revenues
Historic Test
Year Rates
12/31/2022
Removal of
Unbilled,
Surcharges &
Misc
Adjusted
Historic Test
Year Book
Revenue
Revenues
Historic Test
Year Rates
(Schedule 3)
Adjustment 1
Annualization
Year Growth
Customer
Growth from
1/1/23 -
3/31/23
weather usage
adjustment
Eagle Historic
Test Year
Normalization
Normalization
of Phase 1
Rates
Revenue
Present Rates
(1)(2)(3) (4) = (2) + (3) (5)(6)(7)(8)(9)(10)+ (10)
Staff's Final Total 52,427,825 594,543 53,022,368 53,022,368 278,681 - (1,664,176) - 819,334 52,456,207
FOR THE TEST YEAR JANUARY 1, 2022 to DECEMBER 31, 2022
SUMMARY OF STAFF'S FINAL HISTORIC TEST YEAR REVENUES UNDER PRESENT RATES
Revised Exhibit No. 123 Schedule No. 4
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 1 of 1

THIS PAGE INTENTIONALLY LEFT BLANK
Exhibit No. 124 Unused

VEOLIA WATER IDAHO, INC.
CASE VEO-W-22-02
SIXTH PRODUCTION REQUEST OF THE COMMISSION STAFF
Preparer/Sponsoring Witness: Cary/Michaelson
REQUEST NO. 163:
Please explain the customer meter mis-read errors that occurred during calendar year
2022. In addition, please provide:
1. The causes of the issue and the Company's corrective actions.
2. The timeframe and specific months that actual consumption data was impacted.
3. Any corrections that need to be made or have already been made to actual consumption
data for each month from January 1, 2022, through December 31, 2022.
4. A detailed explanation how the Company determined the amount of the corrections for
each month.
5. The Company's final actual customer counts and customer consumption from January
1, 2022, through December 31, 2022, by updating the Company's workpaper file "VEO-
W-22-02 Revenue Exhibits - Workpapers to IPUC STAFF," provided in electronic
format with all formula enabled.
RESPONSE NO. 163:
1. Cause of the issue: Inaccurate meter readings were provided by one meter reader for
approximately 1,019 customers, or less than 1% of the total customer base. The
preliminary number of customers impacted of 1,136 provided informally to Commission
Staff was incorrectly totaled due to duplicate account numbers listed in the tracking file.
2. Timeframe: The bill periods impacted by inaccurate meter readings span from July 2022
through January 2023.
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 1 of 7
Revised Exhibit No. 125
Background information: During December 2022 VWID’s billing staff began receiving
system generated exceptions for potentially problematic meter readings. The pending
bills showed an unusually high water usage amount for that (two-month) billing period
compared to the customer’s prior year usage consumption history for that same period. A
pattern with a single Meter Reader became evident as billing staff reviewed these
customer accounts and found irregularities in generally consistent and predictable
consumption patterns.
All safeguards to ensure meter reading accuracy and validity were in place,
including: company vehicle GPS positions, handheld meter reading device locations and
distances from last reading, acceptable parameters, average time to read the assigned
meter route, and the valid meter reading range (both high and low) based on the
customer’s prior year consumption. While the facts gathered during the investigation did
not reveal whether the employee intentionally falsified meter readings and there was no
admission of such, the company has reason to believe that the Meter Reader did not reach
each customer’s meter (by opening the meter box lid) as they moved through the assigned
meter reading route. The Company suspects the Meter Reader misrepresented meter
readings as actual that were low enough to avoid triggering the aforementioned
acceptable reading safeguards. Due to the number of delayed exceptions triggered and
erratic consumption generated from one Meter Reader’s work, it is the Company’s belief
that this individual was misrepresenting meter readings which were the basis for
customer bills and this required correction. Under-reported consumption from inaccurate
meter readings required rebilling for approximately 1,019 customers, to reallocate actual
consumption to the appropriate periods and true up under-reported water usage.
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 2 of 7
Revised Exhibit No. 125
Rebilling is a necessary step in order for customer usage history to be accurately
reflected for billing purposes, including for customers who use budget billing level-pay
options based on their 12 months of consumption history, as well as for customers who
have their sewer bills based on their wintertime water usage. Rebills are generally done
for one prior billing period, however in this instance it was necessary to rebill customers
for up to 3 billing periods. That determination was made based on the billing staff’s
careful review of the customer’s usage history which indicated that this “mis-read” issue
was not a system error and not isolated to just one period but also that prior meter
readings by the same Meter Reader were suspect as well even though they fell within
acceptable system parameters. These inaccurate readings did not trigger an exception at
that time and were billed as actual readings on customer bills.
Corrective actions: The initial step in addressing meter read exceptions includes
verifying the meter reading by field customer service staff and conducting a leak check if
warranted. After the meter reading is verified as actual with no indication of constant
usage which would indicate a leak, billing staff perform an in-depth review of the
customer’s account to address the cause of the error, and determine whether a cancel-
rebill is warranted. Based on a careful review of the customer’s consumption history and
relying on their expertise, when billing staff determine a rebill is necessary, they cancel
the pending and prior bills(s) and rebill actual usage based on best available information.
Customer service representatives then contacted the affected customer by phone
as the rebillings are generated, rather than relying on the normally mailed customer letter
to inform customers of the extraordinary situation, to answer any questions and advise
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 3 of 7
Revised Exhibit No. 125
that they should expect to see cancel/rebills on their next bill. Customers may request a
payment plan to extend the period they have to pay their bill.
Even though the rebilling(s) represent actual usage for each customer, the
company uses its discretion to provide an appropriate credit to customers with
outstanding concerns when they contact the company or Commission, if they are
burdened financially, unduly inconvenienced, or face hardship as a result. The
Company’s customer service staff work with customers to find an agreeable solution.
The meter reader responsible for the abnormally large number of mis-read meter
readings was placed on unpaid suspension during the investigation and was separated
from the company following completion of the investigation on January 20, 2023.
3. Corrections made to consumption data by month: Verified meter readings for actual
meter reads were completed as of January 24, 2023. Rebillings due to this abnormality in
mis-read meter readings have been processed starting November 29, 2022, with the
majority completed in January 2023, and a few remaining rebills completed in February
2023. Consumption billed by month for system reports are not retroactively restated. Any
consumption and the amount billed difference between prior bills that are subsequently
canceled and rebilled, are reflected in the month when the rebilling takes place. Even
though consumption was “reallocated” to the other billing periods, the subsequent meter
reading and rebilled total captures a true-up of under-reported consumption and
potentially “new” consumption for the current billed period. Bills for bi-monthly billed
customers reflect consumption over a two-month period. The consumption reported for
December 2022 will include rebilled consumption for prior bills that span as far back as
July 2022 in this instance. The canceled and rebilled amounts below reflect 100 cubic
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 4 of 7
Revised Exhibit No. 125
feet (CCF) consumption as well as the total amount billed, which includes: consumptive
fees, meter fees, franchise taxes, safe drinking water fees, surcharges, etc. There are no
retroactive adjustments made to prior month-end consumption or revenue reports.
However based on the company’s analysis the rebilling which took place and based on
available data for 994 rebilled customers resulted in the approximate impact per TABLE
1 below:
TABLE 1
Bill Date (Start - End)
Canceled
Bills
CCF's
Rebilled
CCF's
(with
Consumptio
n True-up)
Cancele
d Bills
Total
Rebilled
Total
CCF
Differenc
e
Billed $
Differenc
e
July - September 2022 -1,206 5,222 -$4,332 $12,681 4,016 $8,348
August - October 2022 -12,582 58,147 -$39,454 $131,592 45,565 $92,138
September - November
2022 -5,837 25,586 -$23,044 $58,371 19,749 $35,327
October - December 2022 -6,505 1,599 -$12,641 $4,695 -4,906 -$7,947
November - January 2023 -8,149 1,877 -$16,692 $6,332 -6,272 -$10,360
TOTAL -34,279 92,431 -$96,163 $213,670 58,152 $117,507
Billed by December 2022
Revenue Cutoff Date -14,643 48,724 -$40,663 $110,756 34,081 $70,093
Billed after December
2022 Revenue Cutoff Date -19,636 43,707 -$55,501 $102,914 24,071 $47,414
TOTAL -34,279 92,431 -$96,163 $213,670 58,152 $117,507
The difference in the count of rebilled accounts of 1,019 compared to the data that
calculated the impact of above for 994 accounts, is due to incorrect account numbers
reflected in the tracking file of 1,019 accounts, and data query limitations. To adjust for
the discrepancy in number of accounts tracked as rebilled versus the available data to
calculate the impact, a gross-up of 1,019 divided by 994 accounts or 1.02515% is applied
and reflected in TABLE 2 Grossed-up below:
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 5 of 7
Revised Exhibit No. 125
TABLE 2 Grossed-up
Bill Date (Start - End)
Bills
CCF's
Rebilled
CCF's
(with
Consumptio
n True-up)
Cancele
d Bills
Total
Rebilled
Total
CCF
Differenc
e
Billed $
Differenc
e
July - September 2022 -1,236 5,353 -$4,441 $12,999 4,117 $8,558
August - October 2022 -12,898 59,609 -$40,447 $134,902 46,711 $94,455
September - November
2022 -5,984 26,230 -$23,623 $59,839 20,246 $36,216
October - December 2022 -6,669 1,639 -$12,959 $4,813 -5,029 -$8,147
November - January 2023 -8,354 1,924 -$17,111 $6,491 -6,430 -$10,620
TOTAL -35,141 94,756 -$98,582 $219,044 59,615 $120,462
Billed by December 2022
Revenue Cutoff Date -15,011 49,949 -$41,685 $113,541 34,938 $71,856
Billed after December
2022 Revenue Cutoff Date -20,130 44,806 -$56,897 $105,503 24,676 $48,606
TOTAL -35,141 94,756 -$98,582 $219,044 59,615 $120,462
Of the 2022 under-reported consumption and revenue plus any “new” usage, 34,938 CCF
of the 59,615 CCF total difference is reflected in year 2022 revenue and consumption
total, while the remainder was rebilled and reflected in year 2023.
4. Explanation for amount of correction: The amount of correction for each rebilling (two
month) period is based on the customer’s unique consumption history. Billing staff
compare the customer’s consumption to the three-year average consumption for the same
time period. During this review they must factor in several variables including:
seasonality, number of billing days in the cycle, historical averages for the same time
period in previous years, how much historical data exists for the current customer and
prior customer of record, is the meter manually read or is an automated meter, previous
reads in the read history, regular reads, estimated reads, and verified reads.
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 6 of 7
Revised Exhibit No. 125
If there are anomalies in the customer’s usage history i.e., unusually high or low
consumption for a particular period and unexplained or uncharacteristic changes in
consumption trends from one bill period to the next, billing staff may exclude those
outliers from the standard three-year average on which the reallocation of usage is based.
If billing staff determine that the customer’s usage history indicates that more than just
one bill period reflected incorrect consumption based on inaccurate meter readings (such
as in this instance) they will analyze and re-allocate customer usage for up to three billing
periods, according to Commission rules.
5. Actual customer counts and customer consumption: In response to staff’s request,
please see the attachment which is an update to the Company Revenue schedules
incorporating the final actual customer counts and customer consumption from January 1,
2022, through December 31, 2022. Please note the attached does not necessarily
represent the Company’s rebuttal position in this case.
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 7 of 7
Revised Exhibit No. 125
ADJUSTMENT R1: ANNUALIZATION OF HISTORIC TEST YEAR GROWTH
1/2 of
Average Usage
per Bill
Annualization
Adjustment
ADJUSTMENT R2: WEIGHTED CUSTOMER GROWTH THROUGH 3/31/2023
Average Usage
per Bill
Growth
Adjustment
Adjustment Not Included in Staff's Proposal
ADJUSTMENT R3: WEATHER USAGE ADJUSTMENT
No.
Customers Customer
Weather
Adjustment
TOTAL OF PRO-FORMA ADJUSTMENTS (R1 + R2 + R3)
No.
Customers
Forma
Adjustment
(773,608)
Number of Customers Number of Bi-
Monthly Bills
SUMMARY OF BILLING DETERMINANTS FOR REVENUE ADJUSTMENTS - VWID SYSTEM
Number of Customers Number of Bi-
Monthly Bills
Revised Exhibit No. 126
Case No. VEO-W-22-02
M. Eldred, Staff
03/01/23 Page 1 of 2
ADJUSTMENT R1: ANNUALIZATION OF HISTORIC TEST YEAR GROWTH
Growth
(use
Gain/Loss
Average Usage
per Bill
Annualization
Adjustment
ADJUSTMENT R2: WEIGHTED CUSTOMER GROWTH THROUGH 3/31/2023
Average Usage
per Bill
Growth
Adjustment
Adjustment Not Included in Staff's Proposal
ADJUSTMENT R3: WEATHER USAGE ADJUSTMENT
No.
Customers Customer
Weather
Adjustment
ADJUSTMENT R4: ANNUALIZATION OF HISTORIC TEST YEAR EXISTING CUSTOMERS
Number of
Customers
Average Usage
per Bill
Annualization
Adjustment
Adjustment Not Included in Staff's Proposal
TOTAL OF TEST YEAR ADJUSTMENTS (R1 + R2 + R3 + R4)
No.
Customers
Total Test Year
Adjustment
(49,491)
Number of
Monthly Bills
(1/2 Year)
Number of Customers Number of
Monthly Bills
SUMMARY OF BILLING DETERMINANTS FOR REVENUE ADJUSTMENTS - EAGLE
Number of Customers Number of
Monthly Bills
Revised Exhibit No. 126
M. Eldred, Staff
03/01/23 Page 2 of 2
EMERGING TRENDS IN WATER RATE-MAKING 95
Customer Classification
The emerging aspect to be addressed in this section is prompted in large part by the greater ability to disaggregate traditional customer classes with better technology that
yields greater data resolution to recognize diversities in traditional classifications. On the wastewater side, this may also involve recognition of the resource recovery value of con­
tributed water streams.
Utilities of the future are not limited to reliance on customer classes of the past. Though traditional customer classes have enabled defensible and equitable cost alloca­
tions, it may be possible to create more precise groupings of customers for rate-making purposes as new information and billing system capabilities evolve. The dramatic increase
in consumption and other customer data (made available, for example, by AMI systems) will empower some utilities to explore a variety of customer class refinements:
•Variability in demand patterns within the residential customer class is oftennot recognized in customer billing systems. It may be desirable to distinguish
between single-family and several different versions of multifamily housing, and
perhaps between different single-family housing units to reflect different peakand average demand characteristics or other water usage determinants (e.g., lot
sizes, plumbing fixture units).
•Commercial, industrial, wholesale, and contract customers exhibit significant
diversity in consumption patterns. Water uses reflect needs ranging from that ofthe proverbial dress shop to a water theme park. Irrigation is a key differentiator,
as it is in residential classes, and equally relevant to cost allocations. The ability tobetter track individual customers' usage characteristics may reveal obvious clus­
tering that suggests new customer classifications or confirms similarities within autility's existing classes.
•Nontraditional customer classification could be structured to address other cus­tomer characteristics beyond those related to metered consumption. In some
cases, customer classes could reflect potential demand, or even desired levels ofdemand, as refinements or extensions to more common demand concepts. In cases
of extreme conservation objectives, some utilities might consider differentiationto reflect the uses to which water is applied, or usage levels determined to be
"excessive" given local supply and cost considerations. Equity and cost allocationissues remain, but improvements in the breadth, quality, and ability to analyze
\ information are stimulating new conversations and examinations.
RATE DESIGN
AWWAManua\Ml
•Utilities could have the potential to identify certain selected affordability criteria
and create an explicit affordability-related class. Challenges and risks associatedwith affordability programs are identified in chapter V.4, but for purposes of thissection, if rates are to be a part of a utility's affordability strategy, customer classi­
fications informed by better information on household demographic characteris­tics could be leveraged.
The "art" of rate-making tends to be seen through the development of structures of rates
and charges that provide for adequate revenue recovery and best meet competing pric­ing objectives. The technological innovations and changing perspectives previously noted
both affect the balancing of objectives and afford new opportunities to send more effective price signals to customers.
Exhibit No. 127 Case No. VEO-W-22-02 M. Eldred, Staff03/01/23
VEOLIA WATER IDAHO,INC. CASE VEO-W-22-02 FIFTH PRODUCTION REQUEST OF THE COMMISSION STAFF
REQUEST NO. 157:
Preparer/Sponsoring Witness: Bui
In Bui's Direct Testimony, page 9, Bui states: "The COSS based total fire demand
on 1 4-hour, 4,500 gallons per minute (gpm) fire, 1 4-hour, 4,000 gpm fire, and 1 2-hour
1,500 gpm fire. This is a change from a total system demand for a 10-hour, 10,000 gpm
fire." Please respond to the following:
a.Please explain why this change was made and provide justification for the
change.
b.Please explain why private fire protection customers were not included in the
Load Study.
RESPONSE NO. 157:
a.Based on the updated cost of service analysis, it was deemed that fire demands should
reflect the actual fire demands that can occur throughout the service area. The service
area has designated fire flow requirements based on the type of customers served. Based
on these requirements, three (3) fires occurring simultaneously were selected as the
appropriate fire flow demand for fire protection. The three fires consist of one 4-hour,
4,500 gpm fire, one 4-hour, 4,000 gpm fire, and one 2-hour 1,500 gpm fire. Prior filings
used a 10-hour, 10,000 gpm fire, which when applied in the cost-of-service analysis
means a single fire that lasts 10 hours and required 10,000 gpm of fire flow. It was Black
& Veatch's opinion that in reality, the system would not see such an occurrence, but
could experience 3 simultaneous fires.
b.Private fire customers were not included in the Load Study as these customers do not
consume water in a similar manner as other customers. Private fire consumption only
occurs during fire events; therefore, consumption data is inconsistent to determine
peaking factors.
Exhibit No. I 28
Case No. VEO-W-22-02 M. Eldred, Staff03/01/23