PNM Resources : Direct Testimony of Dr. J. Stuart McMenamin Load Forecast PNM 2025 Rate Request 24 00089 UT

BEFORE THE NEW MEXICO PUBLIC REGULATION COMMISSION

IN THE MATTER OF THE APPLICATION	)
OF PUBLIC SERVICE COMPANY OF NEW	)
MEXICO FOR REVISION OF ITS RETAIL	)
ELECTRIC RATES PURSUANT TO ADVICE	)
NOTICE NO. 625	) Case No. 24-00089-UT
	)
PUBLIC SERVICE COMPANY OF NEW	)
MEXICO,	)
	)
Applicant	)
	)

DIRECT TESTIMONY

OF

DR. J. STUART MCMENAMIN

June 14, 2024

NMPRC CASE NO. 24-00089-UT

INDEX TO THE DIRECT TESTIMONY OF DR. J. STUART MCMENAMIN

WITNESS FOR

PUBLIC SERVICE COMPANY OF NEW MEXICO

I.	INTRODUCTION AND PURPOSE	1
II.	BACKGROUND AND QUALIFICATIONS	4
III.	RATE CLASSES AND RATE SCHEDULES	5
IV.	MONTHLY RATE CLASS SALES MODELING FRAMEWORK	9
V.	BASE PERIOD WEATHER ADJUSTMENTS	16
VI.	CUSTOMER GROWTH FORECASTS	23
VII.	TEST PERIOD SALES FORECASTS	25
VIII.	FRAMEWORK FOR HOURLY LOAD PROJECTIONS	35
IX.	CLASS NCP, SYSTEM LOAD, AND CLASS CP PROJECTIONS	40

1. BILLING DETERMINANT MODELING FRAMEWORK AND TEST PERIOD

PROJECTIONS	.................................................................................................... 43
XI. CONCLUSION	53
PNM Exhibit SM - 1	Statement of Qualifications
PNM Exhibit SM - 2	Modeling Terminology
SELF AFFIRMATION

i

ABBREVIATION	DESCRIPTION OF ACRONYM OR ABBREVIATION
2022 Rate Case	Case No. 22-00270-UT or the prior rate case
2024 Rate Case	The current rate case or Case No. 24-00089-UT
Base Period	January 2023 through December 2023
CD	Cooling degree. Degrees above a base temperature on a day
CDD	Cooling degree days. Sum of cooling degrees in a month or year
COT	Customer owned transmission
CP	Coincident peak. Customer or class load at time of system peak
DBT	Drybulb temperature
Demand Ratio	Maximum demand divided by average load (inverse of load factor)
EIA	Energy Information Administration, U.S. Department of Energy
EV	Electric Vehicle
GHI	Global horizontal irradiation measured in Watts per square meter
GWH	Gigawatt hour. 1,000 MWh
GP	General Power customer class
HB	Hour beginning (for example 15:00 for 3 PM to 4 PM)
HD	Heating degree. Degrees below a base temperature on a day
HDD	Heating degree days. Sum of heating degrees in a month or year
KWH	Kilowatt hour
KW	Kilowatt
KVA	Kilovolt ampere
Load Factor	Average hourly energy divided by peak load
LED	Light Emitting Diode
LP	Large Power customer class
LS	Large Service customer classes
MWH	Megawatt hour. 1,000 KWH
MW	Megawatt. 1,000 KW
MVA	Megavolt ampere. 1,000 KVA
NCP	Non coincident peak. The maximum load for a customer or class
PAL	Private Area Lighting
PV	Photo voltaic, usually meaning behind-the-meter solar
Pri	Abbreviation for Primary voltage
RKVA	Reactive power in kilovolt amperes
RMVA	Reactive power in megavolt amperes
SAE	Statistically Adjusted End-Use modeling approach
Sales	Net delivered energy (delivered - received)
Sec	Abbreviation for Secondary voltage
SP	Small Power customer class
SPCD	Sales per customer per day
SPD	Sales per day

ii

ABBREVIATION	DESCRIPTION OF ACRONYM OR ABBREVIATION
Test Period	July 2025 through June 2026
TOD	Time of Day
TOU	Time of Use
UPCD	Energy use per customer per day (regardless of source)
UPD	Energy use per day (regardless of source)
Use	Electricity consumed by customer end-use equipment
WHEV	Whole home electric vehicle pilot. Part of rate 1A.

iii

		DIRECT TESTIMONY OF
		DR. J. STUART MCMENAMIN
		NMPRC CASE NO. 24-00089-UT
1	I.	INTRODUCTION AND PURPOSE
2

1. Q. Please state your name, position, and business address.
2. A. My name is John Stuart McMenamin. I am Director of Forecasting at Itron Inc.
3. ("Itron"). My business address is 10870 Rancho Bernardo Road Suite 100, San
4. Diego, CA 92127. A description of my position and background is included in PNM
5. Exhibit SM-1.

8

1. Q. On whose behalf are you testifying in this proceeding?
2. A. My testimony is on behalf of Public Service Company of New Mexico ("PNM" or
3. "Company").

12

1. Q. What is the purpose of your direct testimony in this case?
2. A. The purpose of my testimony is to describe the data and modeling methods that are
3. used to develop Base Period estimates and Test Period projections that support rate-
4. case calculations.

17

1. Q. Please describe your testimony about the Base Period.
2. A. The Base Period is the 12-month period from January 2023 to December 2023. For
3. this period, historical sales and hourly load data are analyzed and modeled to
4. develop the following:

22	•	Weather adjustments for rate class sales in the Base Period;
23	•	Estimates of rate class peaks and loads at the time of the system peak.
		1

DIRECT TESTIMONY OF

DR. J. STUART MCMENAMIN

NMPRC CASE NO. 24-00089-UT

1. The Base Period results provide the starting point for development of projections
2. in the Test Period.

3

1. The modeling approach used to calculate weather adjustments in this rate case is
2. the same as was used in the prior rate case. However, a change was made to the
3. way normal weather is defined. In the prior rate case, normal weather was defined
4. using the prior 20 years of actual weather. In the current case, this has been changed
5. to define normal weather based on the most recent ten years of actual weather (2014
6. through 2023). In 2023, PNM changed to the use of a 10-year normal for
7. development of the Annual Operating Plan, and it was decided to use the same
8. definition for the rate case. The impact of this change is that normal weather in the
9. winter is warmer, which will reduce normal heating loads, and normal weather in
10. the summer is warmer, which will increase normal cooling loads.

14

1. Q. Please describe your testimony about the Test Period.
2. A. The Test Period for this rate case is the 12 months from July 2025 through June
3. 2026.
4. Test Period projections are developed for the following:

19	•	Number of customers by rate class and rate schedule
20	•	Billed sales by rate class and rate schedule
21	•	Billing determinants by rate schedule
22	•	Estimates of rate class peaks and class loads at the time of system peak

2

DIRECT TESTIMONY OF

DR. J. STUART MCMENAMIN

NMPRC CASE NO. 24-00089-UT

1. Test Period estimates of rate class peaks and class loads at the time of system peak
2. are used by PNM in cost allocation calculations that drive revenue requirements by
3. class. Test Period projections of monthly billing determinants are used by PNM to
4. calculate the revenue that can be expected from the proposed rates.

5

1. As my testimony will show, the modeling approach used to generate the Test Period
2. results is the same as in the prior rate case. Of course, the historical sales, weather
3. and load data have been updated to use the most recent information. Also, there
4. are some minor changes:
5. --Inclusion of the Whole House Electric Vehicle ("WHEV") rate option.
6. --Inclusion of the Commercial Charging rate option (General Power Rate

12	Schedule 3F).

1. --Forecasts are based on 10-year normal weather definition.
2. --Forecasts of sales growth for existing industrial customers have been modified

15	to incorporate information provided by the customers.

1. --Growth related to economic development has been modified.
2. My testimony provides an overview of the analysis and modeling methods that are
3. used to develop Test Period results. It also provides tables and charts that present
4. the high-level results.

20

1. Q. Are you sponsoring any Rule 530 schedules?
2. A. Yes. I sponsor Rule 530 Schedules M-3,P-1,P-6, and P-9.

3

		DIRECT TESTIMONY OF
		DR. J. STUART MCMENAMIN
		NMPRC CASE NO. 24-00089-UT
1	II.	BACKGROUND AND QUALIFICATIONS
2

3 Q. Please describe your educational background and professional experience.

4 A. I received my undergraduate degree in Mathematics and Economics from

1. Occidental College in Los Angeles, California in 1971. My post graduate degree
2. is a Ph.D. in Economics from the University of California, San Diego, which I
3. received in 1976. I have worked in the fields of energy forecasting and load
4. research since 1976 and have consulted with many of the major electric and gas
5. utilities in North America. In the 1980's and early 1990's, my work focused on
6. end-usemodeling, and I was the Principal Investigator for the Electric Power
7. Research Institute end-use modeling programs during this period. More recently,
8. my work has focused on methods that combine econometric and end-use concepts.
9. For the last 22 years, I have been employed by Itron, and I am currently Director
10. of the Forecasting Solutions group at Itron. Additional details are available in my
11. resume, which is attached to this testimony as PNM Exhibit SM-1.

16

1. Q. Please describe your duties as Director of Forecasting at Itron.
2. A. For the last 22 years, I have been employed by Itron as Director of the Forecasting
3. Solutions group. During this period, I have managed the development of our
4. Automated Forecasting System, which is used by many large system operators, like
5. the California ISO, Midwest ISO, and ERCOT. Also, I am responsible for Itron
6. products and services related to financial forecasting, including the Itron statistical
7. package (MetrixND), which is used by approximately 200 utilities to forecast

4

DIRECT TESTIMONY OF

DR. J. STUART MCMENAMIN

NMPRC CASE NO. 24-00089-UT

1. customer growth, sales, revenues, and hourly loads. In addition to product design
2. and algorithm development, I manage or contribute to consulting projects related
3. to forecasting and load research for utilities. For the last 15 years, I have been
4. working with utilities in North America to help them improve analysis and

1. forecasting processes using more granular data from advanced metering systems.

7	III.	RATE CLASSES AND RATE SCHEDULES
8

1. Q. Please define customer class as it is used in your testimony.
2. A. Customer classes are high level groupings based on the type of customer, customer
3. size, and the voltage level at which energy is delivered. PNM Table SM-1 provides
4. a list of the customer classes and their definitions. It also provides Base Period data
5. for the number of customers, sales in gigawatt hours ("GWh"), sales per customer
6. ("SPC") in megawatt hours ("MWh"), and the percentage of total sales for each
7. class. The customer and sales data are measured historical data from the customer
8. billing system for the months in the Base Period. Sales are measured in kilowatt
9. hours ("KWh") at the customer premise by electric meters. In my testimony, SPC
10. values are reported in megawatt hours (MWh = 1,000 KWh) and sales levels are
11. reported in gigawatt hours (GWh = 1,000 MWh).

5

DIRECT TESTIMONY OF

DR. J. STUART MCMENAMIN

NMPRC CASE NO. 24-00089-UT

1 PNM Table SM-1: Base Period Customer Class Data

2

3

1. Q. Please define the terms rate schedule and billing determinants as they are used
2. in your testimony.

6 A. Rate schedules divide customer classes into more specific groupings. Rate

1. schedules define the specific prices (called rates) that are applied to measured
2. quantities on a customer bill (called billing determinants). PNM Table SM-2
3. provides a list of the rate schedules for which billing determinant predictions are
4. made. This table also shows the specific billing determinants that are used for each
5. rate schedule. In addition to the billing determinants shown in the table, all rate
6. schedules also include a monthly customer charge. Finally, for the Large Power
7. ("LP") class there is a distinction between customers who have customer-owned
8. transformers (4B-COT) and customers served by PNM owned transformers (4B).

6