20211230IRP Appendix A.pdf

INTEGRATED RESOURCE PLAN
A VIEW FROM ABOVE
2021IRP
DECEMBER • 2021
APPENDIX A: SALES & LOAD FORECAST
Printed on recycled paper
SAFE HARBOR STATEMENT
This document may contain forward-looking statements,
and it is important to note that the future results could
differ materially from those discussed. A full discussion
of the factors that could cause future results to differ
materially can be found in Idaho Power’s filings with the
Securities and Exchange Commission.

Table of Contents
2021 Integrated Resource Plan—Appendix A Page i
TABLE OF CONTENTS
Table of Contents ........................................................................................................................... i
List of Tables ................................................................................................................................. ii
List of Figures ............................................................................................................................... iii
List of Appendices ........................................................................................................................ iii
Introduction .................................................................................................................................. 1
2021 IRP Sales and Load Forecast ................................................................................................. 3
Average Load ........................................................................................................................... 3
Peak-Hour Demands ............................................................................................................... 4
Overview of the Forecast and Scenarios ....................................................................................... 6
Forecast Probabilities .............................................................................................................. 6
Load Forecasts Based on Weather Variability ................................................................... 6
Load Forecasts Based on Economic Uncertainty ............................................................... 8
Company System Load ................................................................................................................ 11
Company System Peak ................................................................................................................ 13
Seasonal Peak Forecast ......................................................................................................... 13
Peak Model Design ................................................................................................................ 16
Class Sales Forecast ..................................................................................................................... 18
Residential ............................................................................................................................. 18
Commercial ........................................................................................................................... 21
Industrial ............................................................................................................................... 26
Irrigation ............................................................................................................................... 29
Additional Firm Load ............................................................................................................. 31
Micron Technology .......................................................................................................... 32
Simplot Fertilizer ............................................................................................................. 32
Idaho National Laboratory .............................................................................................. 32
Anticipated Large-Load Growth ...................................................................................... 33
Table of Contents
Page ii 2021 Integrated Resource Plan—Appendix A
Additional Considerations ........................................................................................................... 34
Energy Efficiency ................................................................................................................... 34
On-Site Generation ............................................................................................................... 35
Electric Vehicles .................................................................................................................... 35
Demand Response ................................................................................................................ 36
Fuel Prices ............................................................................................................................. 37
Other Considerations ............................................................................................................ 39
Hourly Load Forecast ............................................................................................................ 40
Historical IRP Methodology ............................................................................................. 40
2021 IRP Methodology .................................................................................................... 40
Enhancements to Hourly Load Forecasting ..................................................................... 40
Hourly System Load Forecast Design ............................................................................... 41
Contract Off-System Load ........................................................................................................... 43

LIST OF TABLES
Table 1. Average load and peak-demand forecast scenarios .................................................... 7
Table 2. System load growth (aMW) ......................................................................................... 7
Table 3. Forecast probabilities .................................................................................................. 9
Table 4. System load growth (aMW) ....................................................................................... 10
Table 5. System summer peak load growth (MW) .................................................................. 13
Table 6. System winter peak load growth (MW) ..................................................................... 15
Table 7. Residential load growth (aMW) ................................................................................. 18
Table 8. Commercial load growth (aMW) ............................................................................... 22
Table 9. Industrial load growth (aMW) ................................................................................... 26
Table 10. Irrigation load growth (aMW) .................................................................................... 29
Table 11. Additional firm load growth (aMW) .......................................................................... 31
Table 12. Residential fuel-price escalation (2021–2040) (average annual
percent change) ........................................................................................................ 37

Table of Contents
2021 Integrated Resource Plan—Appendix A Page iii
LIST OF FIGURES
Figure 1. Forecast system load (aMW) ................................................................................. 8
Figure 2. Forecast system load (aMW) ............................................................................... 10
Figure 3. Composition of system company electricity sales (thousands of
MWh) ........................................................................................................................ 12
Figure 4. Forecast system summer peak (MW) .................................................................. 14
Figure 5. Forecast system winter peak (MW) ..................................................................... 15
Figure 6. Idaho Power monthly peaks (MW) ...................................................................... 16
Figure 7. Forecast residential load (aMW) ......................................................................... 18
Figure 8. Forecast residential use per customer (weather-adjusted kWh) ......................... 20
Figure 9. Residential customer growth rates (12-month change) ...................................... 20
Figure 10. Residential sales forecast methodology framework .................................................. 21
Figure 11. Forecast commercial load (aMW) ............................................................................. 22
Figure 12. Commercial building share—energy bills .................................................................. 23
Figure 13. Forecast commercial use per customer (weather-adjusted kWh) ............................. 24
Figure 14. Commercial categories UPC, 2020 relative to 2013 ................................................... 25
Figure 15. Forecast industrial load (aMW) ................................................................................. 27
Figure 16. Industrial electricity consumption by industry group (based on
2020 sales)................................................................................................................. 28
Figure 17. Commercial and industrial general sales forecast methodology ............................... 29
Figure 18. Forecast irrigation load (aMW) ................................................................................. 30
Figure 19. Forecast additional firm load (aMW) ......................................................................... 32
Figure 20. Forecast residential electricity prices (cents per kWh) .............................................. 38
Figure 21. Forecast residential natural gas prices (dollars per therm) ....................................... 39
Figure 22. Class Contribution to System Peak ............................................................................ 42

LIST OF APPENDICES
Appendix A1. Historical and Projected Sales and Load ..................................................... 44
Company System Load (excluding Astaris) ............................................................................ 44
Historical Company System Sales and Load, 1980–2020 (weather adjusted) .................. 44
Table of Contents
Page iv 2021 Integrated Resource Plan—Appendix A
Company System Load .......................................................................................................... 45
Projected Company System Sales and Load, 2021–2040 ................................................ 45
Residential Load .................................................................................................................... 46
Historical Residential Sales and Load, 1980–2020 (weather adjusted) ........................... 46
Projected Residential Sales and Load, 2021–2040 .......................................................... 47
Commercial Load .................................................................................................................. 48
Historical Commercial Sales and Load, 1980–2020 (weather adjusted) .......................... 48
Projected Commercial Sales and Load, 2021–2040 ......................................................... 49
Irrigation Load ....................................................................................................................... 50
Historical Irrigation Sales and Load, 1980–2020 (weather adjusted) .............................. 50
Projected Irrigation Sales and Load, 2021–2040 ............................................................. 52
Industrial Load ...................................................................................................................... 52
Historical Industrial Sales and Load, 1980–2020 (not weather adjusted) ........................ 52
Projected Industrial Sales and Load, 2021–2040 ............................................................. 55
Additional Firm Sales and Load ............................................................................................. 56
Historical Additional Firm Sales and Load, 1980–2020 .................................................... 56
Projected Additional Firm Sales and Load, 2021–2040 ................................................... 57
Introduction
2021 Integrated Resource Plan—Appendix A Page 1
INTRODUCTION
Idaho Power has prepared Appendix A—Sales and Load Forecast as part of the 2021 Integrated
Resource Plan (IRP). Appendix A includes details on the energy sales and load forecast of future
demand for electricity within the company’s service area. The above-mentioned forecast covers
a 20-year period from 2021 through 2040.
This appendix describes the development of the anticipated monthly sales forecast.
The forecast is Idaho Power’s estimate of the most probable outcome for sales growth during
the 20-year planning period. In addition, to account for inherent uncertainty in the forecast,
additional forecast cases are prepared to test ranges of variability to the anticipated case.
Economic and demographic (non-weather-related) assumptions are modified to create
scenarios for a low and a high economic-related case. By holding weather variability constant,
these forecasts test the assumptions of the anticipated case economic/demographic variables
by applying historically based parameters of growth on both the low and high side of the
economic determinants of the anticipated case forecast.
Economic data in the forecast models is primarily sourced from Moody’s Analytics and Woods
& Poole Economics. The national, state, metropolitan statistical area (MSA), and county
economic and demographic projections are tailored to Idaho Power’s service area using an
in-house historic economic database. Specific demographic projections are also developed for
the service area from national and local census data. Additional data sources used to
substantiate said economic data include, but are not limited to, the Idaho Department of Labor,
Construction Monitor, and Federal Reserve economic databases.
As economic growth assumptions influence several classes of service growth rates it is
important to review several key components. The number of households in Idaho is projected
to grow at an annual rate of 2% during the forecast period. The growth in the number of
households within individual counties in Idaho Power’s service area is projected to grow faster
than the remainder of the state over the planning period. Similarly, the number of households
in the Boise–Nampa MSA is projected to grow faster than the state of Idaho as well, at an
annual rate of 2.6% during the forecast period. The Boise MSA (or the Treasure Valley) is an
area that encompasses Ada, Boise, Canyon, Gem, and Owyhee counties in southwestern Idaho.
In addition to the number of households, incomes, employment, economic output, and real
retail electricity prices are used to develop load projections.
Scenarios of weather-related influence on potential ranges of the anticipated forecast are
tested utilizing a probabilistic distribution of normal weather (temperature and precipitation)
applied to the weather assumptions in the anticipated case. This provides a comparative range
of outcome that isolates long-term sustained weather influences on the forecast.
Introduction
Page 2 2021 Integrated Resource Plan—Appendix A
The forecast of the anticipated scenario shows, Idaho Power’s system load is forecast to
increase to 2,482 average megawatts (aMW) by 2040 from 1,895 aMW in 2021, representing an
average yearly growth rate of 1.4% over the 20-year planning period (2021–2040). A similar
annual average growth rate in system load is reflected in various weather-related scenarios.
From an annual peak-hour demand perspective, the anticipated case of the peak demand
forecast will grow to 4,700 megawatts (MW) in 2040 from the all-time system peak of
3,751 MW that occurred on Wednesday, June 30, 2021, at 5 p.m. Idaho Power’s system peak
increases at an average growth rate of 1.4% per year over the 20-year planning period
(2021–2040) under this case. Over this same term, the number of Idaho Power active retail
customers is expected to increase from the December 2020 level of 586,071 customers to
nearly 851,849 customers by year-end 2040.
Beyond the weather, climate, economic and demographic assumptions used to drive the
anticipated case forecast scenario, several additional assumptions were incorporated into the
forecasts of the residential, commercial, industrial, and irrigation sectors.
Some examples include conservation influences on the load forecast, including Idaho Power
energy efficiency demand side management (DSM) programs, statutory programs,
and non-programmatic trends in conservation. These influences are included in the load
forecasts. Idaho Power DSM programs are described in detail in Idaho Power’s Demand-Side
Management 2020 Annual Report, which is incorporated into this IRP document as Appendix B.
Idaho Power also recognizes the impact of on-site generation and electric vehicles in its service
territory and does include the energy reduction or addition in the long-term sales and load
forecast due to their impact. Further discussions of these assumptions are presented in the
appropriate section.
Outside of weather, potential primary risks during the 20-year forecast horizon include major
shifts in the electric utility industry (e.g., state and federal regulations and varying electricity
prices) which could influence the load forecast. In addition, the price and volatility of substitute
fuels, such as natural gas, may also impact future demand for electricity. The uncertainty
associated with such changes is reflected in the economic high and low load growth scenarios
described previously. The alternative sales and load scenarios in Appendix A—Sales and Load
Forecast were prepared under the assumption that Idaho Power’s geographic service area
remains unchanged during the planning period.
Data describing the historical and projected figures for the sales and load forecast are
presented in Appendix A1 of this report.
2021 Sales and Load Forecast
2021 Integrated Resource Plan—Appendix A Page 3
2021 IRP SALES AND LOAD FORECAST
Average Load
The economic and demographic variables driving the 2021 forecast have the impact of
increasing current annual sales levels throughout the planning period. The extended business
cycle recovery process after the Great Recession in 2008 for the national and service area
economy muted load growth post-recession through 2011. However, in 2012, the extended
recovery process was evident, and on-balance stronger growth was exhibited in most economic
drivers relative to post Great Recession history. From that point, the global pandemic recession
in 2020 had profound effects across the national and global economy. For the company,
residential sales increased approximately 5% in 2020 and into 2021. This growth is attributable
to both work-from-home edicts as well as continued strong in-migration trends.
Negative energy use was initially exhibited by the commercial and industrial classes but have
since stabilized and, overall, rebounded quickly. Irrigation sales were mostly unaffected by the
pandemic. It is expected that economic conditions return to long-term fundamentals during the
2021 IRP forecast term. COVID-19 impacts are further discussed in the individual class sections
below. Additional significant factors and considerations that influenced the outcome of the
2021 IRP load forecast include the following:
• Weather plays a primary role in impacting the load forecast on a monthly and seasonal
basis. In the anticipated case load forecast of energy and peak-hour demand,
Idaho Power assumes average temperatures and precipitation over a 30-year
meteorological measurement period or defined as normal climatology.
Probabilistic variations of weather are also analyzed.
• The economic forecast used for the 2021 IRP reflects the continued expansion of the
Idaho economy in the near-term and reversion to the long-term trend of the service
area economy. Customer growth was at a near standstill until 2012, but since then
acceleration of net migration and business investment has resulted in renewed positive
activity. The state of Idaho had the highest residential population growth rate of any
state in the United States over the past 5 years (ending 2020). Customer additions
experienced prior to the housing bubble are expected to continue.
• Conservation impacts, including DSM energy efficiency programs, codes, and standards,
and other naturally occurring efficiencies are integrated into the sales forecast.
These impacts are expected to continue to erode use per customer over much of the
forecast period. Impacts of demand response programs (on peak) are accounted for in
the load and resource balance analysis within supply-side planning
(i.e., demand response is treated as a supply-side peaking resource). The amount of
committed and implemented DSM programs for each month of the planning period is
2021 Sales and Load Forecast
Page 4 2021 Integrated Resource Plan—Appendix A
shown in the load and resource balance in Appendix C—Technical Appendix. Additional
impacts from on-site generation customers and electric vehicles are included as well.
• Although interest from large customers has been robust, there is some uncertainty
associated with these industrial and special contract customers due to the number of
parties that contact Idaho Power expressing interest in locating operations within
Idaho Power’s service area, typically with an uncertain magnitude of the energy and
peak-demand requirements. The anticipated load forecast reflects only those industrial
customers that have made a sufficient and significant binding investment and/or
interest indicating a commitment of the highest probability of locating in the service
area. The large numbers of prospective businesses that have indicated some interest in
locating in Idaho Power’s service area but have not made sufficient commitments are
not included in the anticipated sales and load forecast.
• The electricity price forecast used to prepare the sales and load forecast in the 2021 IRP
reflects the additional plant investment and variable costs of integrating the resources
identified in the 2019 IRP preferred portfolio. When compared to the electricity price
forecast used to prepare the 2019 IRP sales and load forecast, the 2021 IRP price
forecast yields lower future prices. The retail prices are mostly lower throughout the
planning period which can impact the sales forecast, a consequence of the inverse
relationship between electricity prices and electricity demand.
• As discussed above, the response to the novel corona virus influenced electric usage
behavior across the major rate classes. Discernably, these impacts tended to balance
one another; e.g., increased residential consumption due to work-from-home behavior
was offset by decreased use from office and other commercial facilities. While these
impacts continue to play out in decreasing importance, the impact on the long-term
forecast horizon is essentially inconsequential.
Peak-Hour Demands
Average loads, as discussed in the preceding section, are an integral component to the load
forecast, as is the impact of the peak-hour demands on the system. Like the sales forecast
discussed in the preceding section, the peak models incorporate several peak forecast scenarios
based on historical probabilities of peak day temperatures at the 50th, 90th, and 95th-percentiles
of occurrence for each month of the year. The peak-hour demands (peaks) are forecasted
separately using regressions that are expressed as a function of the sales (average load)
forecast as well as the impact of peak-day temperatures, more discussion is provided in
forthcoming sections.
2021 Sales and Load Forecast
2021 Integrated Resource Plan—Appendix A Page 5
The peak forecast results and comparisons with previous forecasts differ for many reasons that
include the following:
• The all-time system summer peak demand was 3,751 MW, recorded on Wednesday,
June 30, 2021, at 7 p.m. The previous all-time system summer peak demand, adjusted
for demand response, was 3,437 MW, recorded on Friday, July 2, 2013, at 5 p.m.
Idaho Power’s winter peak-hour load record is 2,527 MW, recorded on January 6, 2017,
at 9 a.m. and matched the previous record peak dated December 10, 2009, at 8 a.m.
• The peak model develops peak-scenario impacts based on historical probabilities of
peak day temperatures at the 50th, 90th, and 95th-percentiles of occurrence for each
month of the year. These average peak-day temperature drivers are calculated over the
1991 to 2020 time period (the most recent 30 years).
• The 2021 IRP peak-demand forecast considers the impact of the current actualized
committed and implemented energy efficiency DSM programs on peak demand.

Overview of the Forecast and Scenarios
Page 6 2021 Integrated Resource Plan—Appendix A
OVERVIEW OF THE FORECAST AND SCENARIOS
The sales and load forecast are constructed by developing a separate energy forecast for each
of the major customer classes: residential, commercial, irrigation, industrial, and special
contracts. In conjunction with this load (or sales) forecast, an hourly peak-load (peak)
forecast was prepared. In addition, several probability cases were developed for the energy and
peak forecasts. Assumptions for each of the individual categories, the peak hour impacts,
and probabilistic case methodologies are described in greater detail in the following sections.
Forecast Probabilities
Load Forecasts Based on Weather Variability
The future demand for electricity by customers in Idaho Power’s service area is represented by
three load forecasts reflecting a range of load uncertainty due to weather. The anticipated
average load forecast represents the most probable projection of system load growth during
the planning period and is based on the most recent national, state, MSA, and county economic
forecasts and the resulting derived economic forecast for Idaho Power’s service area.
The anticipated average load forecast assumes median temperatures and median precipitation
(i.e., there is a 50% chance loads will be higher or lower than the anticipated loads due to
colder-than-median or hotter-than-median temperatures or wetter-than-median or
drier-than-median precipitation). Since actual loads can vary significantly depending on
weather conditions, alternative scenarios were developed that address load variability due to
varying weather conditions.
Illustratively, Idaho Power’s maximum annual average load occurs when the highest recorded
levels of heating degree days (HDD) are assumed in winter and the highest recorded levels of
cooling and growing degree days (CDD and GDD) combined with the lowest recorded level of
precipitation are assumed in summer. Conversely, the minimum annual average load occurs
when the opposite of what is described above takes place. In the 70th-percentile residential and
commercial load forecasts, temperatures in each month were assumed to be at the
70th-percentile of HDD in wintertime and at the 70th-percentile of CDD in summertime. In the
70th-percentile irrigation load forecast, GDD were assumed to be at the 70th-percentile and
precipitation at the 30th-percentile, reflecting drier-than-median weather. The 90th-percentile
load forecast was similarly constructed.
For example, the median HDD in December from 1991 to 2020 (the most recent 30 years)
was 1,024 at the Boise Weather Service office. The 70th-percentile HDD is 1,048 and would be
exceeded in 3 out of 10 years. The 90th-percentile HDD is 1,130 and would be exceeded in 1 out
of 10 years. As an example, for a single month, the near 100th-percentile HDD (the coldest
December over the 30 years) is 1,284, which occurred in December 2016. This same concept

Overview of the Forecast and Scenarios
2021 Integrated Resource Plan—Appendix A Page 7
was applied in each month throughout the year for the weather-sensitive customer classes:
residential, commercial, and irrigation.
Since Idaho Power loads are highly dependent on weather, and the development of the above
mentioned two scenarios allows the careful examination of load variability and how it may
impact future resource requirements, it is important to understand that the probabilities
associated with these forecasts apply to each month. This assumes temperatures and
precipitation would maintain at the 70th-percentile or 90th-percentile level continuously,
throughout the entire year. Table 1 summarizes the load scenarios prepared for the 2021 IRP.
Table 1. Average load and peak-demand forecast scenarios
Weather Probability Exceeding

90th Percentile 90%
70th Percentile 70%
Anticipated Case 50%
Forecasts of Peak Demand
95th Percentile 95% -day temperatures
90th Percentile 90% -day temperatures
50th Percentile 50% -day temperatures

Results of Idaho Power’s weather-related probabilistic system load projections are reported in
Table 2 and shown in Figure 1.

Table 2. System load growth (aMW)
Growth 2021 2025 2030 2040
Annual Growth Rate
2021–2040
90th Percentile ............................................................. 2,001 2,197 2,427 2,620 1.4%
70th Percentile ............................................................. 1,941 2,132 2,357 2,541 1.4%
Anticipated Case .......................................................... 1,895 2,082 2,304 2,482 1.4%

Overview of the Forecast and Scenarios
Page 8 2021 Integrated Resource Plan—Appendix A
Figure 1. Forecast system load (aMW)1
Load Forecasts Based on Economic Uncertainty
The anticipated load forecast is based on the most recent economic forecast for Idaho Power’s
service area and represents Idaho Power’s most probable outcome for load growth during the
planning period.
To provide risk assessment to economic uncertainty, two additional load forecasts for
Idaho Power’s service area were prepared based on the anticipated case forecast. The forecasts
provide a range of possible load growth rates for the 2021 to 2040 planning period due to high
and low economic and demographic conditions. The average growth rates for these high and
low growth scenarios were derived from the historical distribution of one-year growth rates
over the past 25 years (1996–2020).
Of the three scenarios 1) the anticipated forecast is the median growth path, 2) the standard
deviation observed during the historical time is used to estimate the dispersion around the
anticipated scenario, and 3) the variation in growth rates will be equivalent to the variation in
growth rates observed over the past 25 years (1996–2020).
From the above methodology, two views of probable outcomes form the forecast
scenarios—the probability of exceeding and the probability of occurrence—were developed

1 The Astaris elemental phosphorous plant (previously FMC) was located at the western edge of Pocatello, Idaho.
Although no longer a customer of Idaho Power, Astaris had been Idaho Power’s largest individual customer and,
in some years, averaged nearly 200 aMW each month. In April 2002, the special contract between Astaris and
Idaho Power was terminated.
700
1,000
1,300
1,600
1,900
2,200
2,500
2,800
1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
Anticipated Case 70th Percentile 90th Percentile
WA less Astaris Weather Adjusted

Overview of the Forecast and Scenarios
2021 Integrated Resource Plan—Appendix A Page 9
and are reported in Table 3. The probability of exceeding the likelihood the actual load growth
will be greater than the projected growth rate in the specified scenario. For example, over the
next 20 years, there is a 10% probability the actual growth rate will exceed the growth rate
projected in the high scenario; additionally, it can be inferred that for the stated periods there
is an 80% probability the actual growth rate will fall between the low and high scenarios.
The second probability estimate, the probability of occurrence, indicates the likelihood the
actual growth will be closer to the growth rate specified in that scenario than to the growth
rate specified in any other scenario. For example, there is a 26% probability the actual growth
rate will be closer to the high scenario than to any other forecast scenario for the entire 20-year
planning horizon.
Table 3. Forecast probabilities
Probability of Exceeding
Scenario 1-year 5-year 10-year 20-year
Low Growth ........................................................................................ 90% 90% 90% 90%
Anticipated Case ................................................................................ 50% 50% 50% 50%
High Growth ....................................................................................... 10% 10% 10% 10%
Probability of Occurrence
Scenario 1-year 5-year 10-year 20-year
Low Growth ........................................................................................ 26% 26% 26% 26%
Anticipated Case ................................................................................ 48% 48% 48% 48%
High Growth ....................................................................................... 26% 26% 26% 26%

This probabilistic analysis was applied to Idaho Power’s system load forecast. Its impact on the
system load forecast is the sum of the individual loads of residential, commercial, industrial,
and irrigation customers, as well as special contracts (including past sales to Astaris, Inc.
[aka FMC]) and on system contracts (including past sales to Raft River Coop and the City
of Weiser).
Results of Idaho Power’s economic scenario probabilistic system load projections are reported
in Table 4 and shown in Figure 2. The anticipated system load-forecast growth rate averages
1.4% per year over the 20-year planning period. The low scenario projects the system load will
increase at an average rate of 1.1% per year throughout the forecast period. The high scenario
projects a load growth of 1.8% per year. Idaho Power has experienced both the high- and
low-growth rates in the past. These forecasts provide a range of projected growth rates that
cover approximately 80% of the probable outcomes as measured by Idaho Power’s
historical experience.

Overview of the Forecast and Scenarios
Page 10 2021 Integrated Resource Plan—Appendix A
Table 4. System load growth (aMW)
Growth 2021 2025 2030 2040 Annual Growth Rate 2021–2040
Low ............................................................................. 1,859 1,991 2,166 2,277 1.1%
Anticipated ................................................................. 1,895 2,082 2,304 2,482 1.4%
High ............................................................................ 1,942 2,190 2,461 2,731 1.8%

Figure 2. Forecast system load (aMW)
800
1,000
1,200
1,400
1,600
1,800
2,000
2,200
2,400
2,600
2,800
1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
Weather Adjusted (excluding Astaris)Anticipated Case High Low

Company System Load
2021 Integrated Resource Plan—Appendix A Page 11
COMPANY SYSTEM LOAD
System load is the sum of the individual loads of residential, commercial, industrial,
and irrigation customers, as well as special contracts (including past sales to Astaris) and system
contracts (including past sales to Raft River and the City of Weiser). The system load excludes all
long-term, firm off-system contracts.
The anticipated system load forecast is based on the output of the regression and forecasting
models referenced previously and represents Idaho Power’s most probable load growth during
the planning period. The load growth of the anticipated system forecast averages 1.4% per year
from 2021 to 2040. Company system load projections are reported in Table 2 and shown in
Figure 1.
In the anticipated forecast, the company system load is expected to increase from 1,895 aMW
in 2021 to 2,482 aMW in 2040, an average annual growth rate of 1.4%. In the weather sensitive
scenarios, the 70th-percentile and 90th-percentile forecasts, the company system load is
expected to increase from 1,941 aMW in 2021 to 2,541 aMW by 2040 and increase from 2,001
aMW in 2021 to 2,620 aMW, respectively. All scenarios have an average growth rate of 1.4%
per year over the planning period. In the economic probability scenarios, the company system
load is expected to increase in the low case from 1,859 aMW in 2021 to 2,277 aMW in 2040,
an average annual growth rate of 1.1% and in the high case from 1,942 aMW to 2,731 aMW,
an average annual growth rate of 1.8% (Table 2).
The system load, excluding Astaris (formerly known as FMC), portrays the current underlying
general business growth trend within the service area. However, the system load with Astaris is
instructive regarding the impact of a loss or gain of a significant large-load customer on
system load.
Accompanied by the outlook of economic growth for Idaho Power’s service area throughout
the forecast period, continued growth in Idaho Power’s system load is expected. Total load is
made up of system load plus long-term, firm, off-system contracts. Currently, there are no
contracts in effect to provide long-term, firm energy off-system.
The composition of system company electricity sales by year is shown in Figure 3.
Residential sales are forecast to be about 16% higher in 2040, gaining 0.9 million
megawatt-hours (MWh) over 2021. Commercial sales are expected to be 19% higher,
or 0.8 million MWh, followed by industrial (35% higher, or 0.9 million additional MWh)
and irrigation (12% higher in 2040 than 2021). Additional firm sales are expected to more than
triple by 2040, gaining 2.1 million MWh over 2021.
In addition to the above anticipated sales forecast, differing weather probabilities, high and low
economic cases, and alternative sales and load cases were developed for analysis within the

Company System Load
Page 12 2021 Integrated Resource Plan—Appendix A
2021 IRP. These include high growth within commercial and industrial classification of an
additional approximate 250 MW of capacity requirements, high penetration future of building
and transportation electrification, and future potential climate change impacts to the
load forecast.
Figure 3. Composition of system company electricity sales (thousands of MWh)
0
4,000
8,000
12,000
16,000
20,000
24,000
1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
Residential Commercial Industrial Irrigation Additional Firm Sales Astaris

Company System Peak
2021 Integrated Resource Plan—Appendix A Page 13
COMPANY SYSTEM PEAK
System peak load includes the sum of the coincident peak demands of residential,
commercial, industrial, and irrigation customers, as well as special contracts (including Astaris,
historically) and on-system contracts (Raft River and the City of Weiser, historically).
Seasonal Peak Forecast
Idaho Power has two peak periods: 1) a winter peak, resulting primarily from space-heating
demand that normally occurs in December, January, or February and 2) a larger summer peak
that normally occurs in late June, July, or August, which coincides with cooling load and
irrigation pumping demand. The summer peak is reflective of the annual peak for the company.
The all-time system summer peak demand was 3,751 MW, recorded on Wednesday, June 30,
2021, at 7 p.m. The previous all-time system summer peak demand, adjusted for demand
response, was 3,437 MW, recorded on Friday, July 2, 2013, at 5 p.m. The system summer peak
load growth accelerated from 1998 to 2008 as a record number of residential, commercial,
and industrial customers were added to the system and air conditioning (A/C) became standard
in nearly all new residential homes and new commercial buildings.
In the 95th-percentile forecast, the system summer peak load is expected to increase from
3,771 MW in 2021 to 4,868 MW in 2040. In the 90th-percentile forecast, the system summer
peak load is expected to increase from 3,745 MW in 2021 to 4,842 MW in 2040. Finally, in the
50th-percentile, or anticipated case, the system summer peak load increases from 3,603 MW in
2021 to 4,700 MW in 2040. All of which represent an average summer peak growth rate of
1.4% per year over the planning period (Table 5).
Table 5. System summer peak load growth (MW)
Growth 2021 2025 2030 2040
Annual
Growth Rate 2021–2040
95th Percentile.............................................................. 3,771 4,071 4,421 4,868 1.4%
90th Percentile ............................................................. 3,745 4,045 4,394 4,842 1.4%
50th Percentile ............................................................. 3,603 3,903 4,252 4,700 1.4%

The three scenarios of projected system summer peak loads are illustrated in Figure 4. Much of
the variation in peak load is due to weather conditions. Note that unique economic events have
occurred, as an example in the summer of 2001 the summer peak was dampened by a nearly
30% curtailment in irrigation load due to a voluntary load reduction program.

Company System Peak
Page 14 2021 Integrated Resource Plan—Appendix A

Figure 4. Forecast system summer peak (MW)
As of December 31, 2019, the all-time system winter peak demand of 2,527 MW, realized on
Thursday, December 10, 2009, at 8 a.m. was matched on January 6, 2017, at 9 a.m. As shown in
Figure 5, the historical system winter peak load is much more variable than the summer system
peak load. This is because the variability of peak-day temperatures in winter months is greater
than the variability of peak-day temperatures in summer months. The wider spread of the
winter peak forecast lines in Figure 5 illustrates the higher variability associated with winter
peak-day temperatures.
In the 95th-percentile forecast, the system winter peak load is expected to increase from
2,699 MW in 2021 to 3,328 MW in 2040, an average growth rate of 1.1% per year over the
planning period. In the 90th-percentile forecast, the system winter peak load is expected to
increase from 2,584 MW in 2021 to 3,262 MW in 2040, an average growth rate of 1.2% per year
over the planning period. In the 50th-percentile, or anticipated case forecast, the system winter
peak load is expected to increase from 2,367 MW in 2021 to 3,132 MW in 2040, an average
growth rate of 1.5% per year over the planning period. This data is represented in Table 6.
The three scenarios of projected system winter peak load are illustrated in Figure 5.2

2 Idaho Power uses a median peak-day temperature driver in lieu of an average peak-day temperature driver in the
50/50 peak-demand forecast scenario. The median peak-day temperature has a 50% probability of being
exceeded. Peak-day temperatures are not normally distributed and can be skewed by one or more extreme
observations; therefore, the median temperature better reflects expected temperatures within the context of
probabilistic percentiles. The weighted average peak-day temperature drivers are calculated over the 1991 to
2020 time (the most recent 30 years).
1,000
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Company System Peak
2021 Integrated Resource Plan—Appendix A Page 15

Table 6. System winter peak load growth (MW)
Growth 2021 2025 2030 2040
Annual Growth Rate
2021–2040
95th Percentile ....................................................................... 2,699 2,918 3,142 3,328 1.1%
90th Percentile ....................................................................... 2,584 2,803 3,028 3,262 1.2%
50th Percentile ....................................................................... 2,367 2,586 2,878 3,132 1.5%

Figure 5. Forecast system winter peak (MW)
Combining the historic relationship of summer and winter peaks as depicted in Figure 6,
the growth in the summer peak over the past several decades in Idaho Power’s service
territory, as evidenced by the shift in the most-recent slope lines, has been significantly greater
due to the increased presence of urban cooling load in the peak summer months.
1,000
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1985-86 1990-91 1995-96 2000-01 2005-06 2010-11 2015-16 2020-21 2025-26 2030-31 2035-36 2040-41
Actual Actual less Astaris 50th Percentile 90th Percentile 95th Percentile

Company System Peak
Page 16 2021 Integrated Resource Plan—Appendix A
Figure 6. Idaho Power monthly peaks (MW)
Note that the 2021 IRP peak-demand forecast model explicitly excludes the impact of demand
response programs to establish peak impacts. The exclusion allows for planning for demand
response programs and supply-side resources in meeting peak demand without the
interference of load intervention on causal variables. Demand response program impacts are
accounted for in the IRP load and resource balance and are reflected as a reduction in
peak demand.
Peak Model Design
Peak-hour demands are integral components to the company’s system planning. Peak-hour
demands are forecast using a system of 12 regression equations, one for each month of the
year. For most monthly models the regressions are estimated using 25 years of historical data,
however, the estimation periods vary. The peak-hour forecasting regressions express system
peak-hour demand as a function of calendar sales (stated in average megawatts) as well as the
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
-40 -20 0 20 40 60 80 100
MW
Avg Daily Temp (system weighted)
'80 '90 '00 '10

Company System Peak
2021 Integrated Resource Plan—Appendix A Page 17
impact of peak-day temperatures, real electricity prices, and in some months precipitation.
The contribution to the system peak of the company’s three special contract customers is
determined independently, using historical coincident peak factors, and then added to
determine the system peak.
The forecast of average peak-day temperatures is a key driver of the monthly system peak
models. The normal average peak-day temperature drivers are calculated over the 1991 to
2020 period (the most recent 30 years). In addition, the peak model develops peak scenarios
based on historical probabilities of peak day temperatures at the 50th, 90th, and 95th percentiles
of occurrence for each month of the year.
Note the summertime (June, July, and August) system peak regression models were
re-specified to account for the upward trend in weighted average peak-day temperatures over
time. The trendlines were fitted to the historical weighted average peak-day temperatures and
then projected through the end of the forecast period, the year 2040. These are added as
explanatory variables in the summertime regression models. The addition of these variables
resulted in models that better fit the actual historical summertime system peaks.

Class Sales Forecasts
Page 18 2021 Integrated Resource Plan—Appendix A
CLASS SALES FORECAST
Residential
The anticipated residential load is forecast to increase from 644 aMW in 2021 to 743 aMW
in 2040, an average annual compound growth rate of 0.8%. In the 70th-percentile scenario,
the residential load is forecast to increase from 664 aMW in 2021 to 773 aMW in 2040,
an average annual compound growth rate of 0.8%, matching the anticipated residential growth
rate. The residential load forecasts are reported in Table 7 and shown in Figure 7.
Table 7. Residential load growth (aMW)
Growth 2021 2025 2030 2040 Annual Growth Rate 2021–2040
90th Percentile ...................................................................... 691 723 746 812 0.9%
70th Percentile ...................................................................... 664 692 712 773 0.8%
Anticipated Case ................................................................... 644 670 687 743 0.8%

Figure 7. Forecast residential load (aMW)
Sales to residential customers made up 30% of Idaho Power’s system sales in 1990 and 37% of
system sales in 2020. The number of residential customers is projected to increase to nearly
719,500 by December 2040.
The average sales per residential customer increased to nearly 14,800 kilowatt-hours (kWh)
in 1980 before declining to 13,200 kWh in 2001. In 2002, residential use per customer dropped
0
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1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
Weather Adjusted Anticipated Case 70th Percentile 90th Percentile

Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 19
dramatically—over 500 kWh per customer from 2001—the result of significantly higher
electricity prices combined with a weak national and service area economy. The reduction in
electricity prices in June 2003 and a recovery in the service-area economy caused residential
use per customer to stabilize through 2007. However, conservation efforts have placed
downward pressure on residential use per customer since that point. This trend is expected to
continue, declining at 1.1% per year, as the average sales per residential customer are expected
to decrease to approximately 9,100 kWh per year by 2040. Average annual sales per residential
customer are shown in Figure 8. Although, it is important to note—as evident in figures 7
and 8—the impacts of the COVID pandemic on residential electricity sales (Figure 7)
and residential use-per-customer (Figure 8). Major shifts in early 2020 to working and schooling
from home, which required retooling homes with computers and electronics, served to boost
residential electricity sales and use-per-customer. Residential sales (weather-adjusted) were 4%
to 5% higher in 2020 than 2019. In addition to the overall increase in use per customer,
the pandemic accelerated in-migration allowing those searching for affordable housing, a more
reasonable cost of living, and ability to work from home to move from larger, more populated
metro areas. This impact is fortified by Idaho having the highest population growth rate of any
state in the United States over the past 5 years (ending 2019)3 which continues today,
as evidenced by Idaho Power’s strong customer growth through year-to-date 2021.

3 United States Census Bureau Population, Population Change, and Estimated Components of Population Change
2010 to 2019.

Class Sales Forecasts
Page 20 2021 Integrated Resource Plan—Appendix A
Figure 8. Forecast residential use per customer (weather-adjusted kWh)
Residential customer growth in Idaho Power’s service area is a function of the number of new
service-area households as derived from Moody’s Analytics’ forecast of county housing stock
and demographic data. The residential-customer forecast for 2021 to 2040 shows an average
annual growth rate of 1.9% as shown in Figure 9.
Figure 9. Residential customer growth rates (12-month change)
Final sales to residential retail customers can be framed in an equation that considers several
factors affecting electricity sales to the residential sector. Residential sales are a function of
5,000
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Actual Forecast
0.0%
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1986 1992 1998 2004 2010 2016 2022 2028 2034 2040
Actual Customers Forecast

Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 21
HDD (wintertime); CDD (summertime); historic energy efficiency trends in Idaho Power’s
residential customer base; saturation and replacement cycle of appliances; the number of
service-area households; the real price of electricity; and the real price of natural gas to name a
few. A general schematic of the forecasting methodology using a statistically adjusted end-use
(SAE) forecast model as described above that is used in Idaho Power’s forecast residential sales
is provided in Figure 10.
Figure 10. Residential sales forecast methodology framework
Further, there were several instances in the SAE framework where the overall outcomes could
benefit from the inclusion of indicator variables. In assessing these and combination thereof,
Idaho Power selected the best statistical result across a menu of options using cross
validation methods.
Commercial
The commercial category is primarily made up of Idaho Power’s small general-service and large
general-service customers. Additional customer types associated with this category include
small general-service on-site generation, customer energy production net-metering,
unmetered general service, street-lighting service, traffic-control signal lighting service,
and dusk-to-dawn customer lighting.
Within the anticipated scenario, the commercial load is projected to increase from 475 aMW in
2021 to 564 aMW in 2040 (Table 8). The average annual compound-growth rate of the
Residential
Sales
Forecast

Class Sales Forecasts
Page 22 2021 Integrated Resource Plan—Appendix A
commercial load in the anticipated scenario is 0.9% during the forecast period. The commercial
load in the 70th-percentile scenario is projected to increase from 481 aMW in 2021 to 572 aMW
in 2040. The commercial load forecast scenarios are illustrated in Figure 11.
Table 8. Commercial load growth (aMW)
Growth 2021 2025 2030 2040
Annual Growth Rate
2021–2040
90th Percentile ....................................................................... 489 515 535 585 0.9%
70th Percentile ....................................................................... 481 505 524 572 0.9%
Anticipated Case .................................................................... 475 499 517 564 0.9%

Figure 11. Forecast commercial load (aMW)
With a customer base of over 75,500, the commercial class represents the diversity of the
service area economy, ranging from residential subdivision pressurized irrigation to large
manufacturers. Due to this diversity in load intensity and use—for analytical purposes—
the category is segmented into categories associated with common elements of energy-use
influences, such as economic variables (e.g., employment), industry (e.g., manufacturing),
and building structure characteristics (e.g., offices). Figure 12 shows the breakdown of the
categories and their relative sizes based on 2020 billed energy sales.
0
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1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
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Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 23
Figure 12. Commercial building share—energy bills
As indicated in Figure 12, agricultural-related, food sales, and the retail goods and service
providers of the mercantile category represent nearly half of the sector. Recent trends in the
sector show that mercantile growth has moderated. This moderation is primarily due to
customer consolidation, growth in internet-based sales, energy efficient retrofitting,
and new-construction technology implementation (particularly around lighting).
Categories showing significant growth over the past 5 years are reflective of the changing
profile of economic and demographic growth in the service territory. Residential growth has led
to a construction boom that has seen construction energy use grow by 10% per year.
Agricultural and manufacturing operations continue to migrate and flourish with growth rates
of 2.2% and 2.5% respectively.
The number of commercial customers is expected to increase at an average annual rate of
1.8%, reaching approximately 107,000 customers by December 2040.
In 1990, customers in the commercial category consumed approximately 18% of Idaho Power
system sales, growing to 27% by 2020. This share is forecast to remain at the upper end of this
range throughout the planning period.
Figure 13 shows historical and forecast average use per customer (UPC) for the entire category.
The commercial-use-per-customer metric in Figure 13 represents an aggregated metric for a
highly diverse group of customers with significant differences in total energy use per customer,
nonetheless it is instructive in aggregate for comparative purposes.
Agricultural
12%Assembly
4%
Communication,
3%
Construction, 1%Education
4%
Office, 26%
Other, 2%
Health, 2%
Mercantile
18%
Food_Sales
20%
Lodging, 2%

Class Sales Forecasts
Page 24 2021 Integrated Resource Plan—Appendix A
The UPC peaked in 2001 at 67,800 kWh and has declined at approximately 1.1% compounded
annually to 2020. The UPC is forecast to decrease at an annual rate of 0.9% over the planning
period. For this category, common elements that drive use down include a shift toward
service-based over industrial customer dominance, adoption of energy efficiency technology,
and electricity prices.
Figure 13. Forecast commercial use per customer (weather-adjusted kWh)
Figure 14 shows the diversity in the commercial segment’s UPC as well as the trend for these
sectors. The figure shows the 2020 UPC for each segment relative to the 2013 UPC. A value
greater than 100% indicates the UPC has risen over the period. The figure supports the general
decline of the aggregated trend of Figure 13 but highlights differences in energy and economic
dynamics within the heterogeneous commercial category not evident in the residential
category. The decline in Figure 14 is also significantly exacerbated by the COVID-19 crisis,
which saw many commercial customer segments close or significantly limit operations during
2020. The subsequent reduction in energy use during this period varied by segment,
however they were concentrated in the service-oriented customers—particularly Education,
Office, Lodging, Restaurant, and Mercantile segments. The models and independent analysis
have shown a significant and ongoing rebound to normal energy use profiles in 2021 for the
commercial sector. The recovery is expected to be complete by the first quarter of 2022.
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
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Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 25
Figure 14. Commercial categories UPC, 2020 relative to 2013
Energy efficiency implementation is a large determinant in UPC decline over time. In the
commercial sector, the primary DSM technology impact has come from lighting,
however manufacturing motors are significant for that sector. Understandably, aggressive DSM
measures can reduce a customer’s usage to trigger a rate-class change from industrial to
commercial class. These shifts are evident in the chart (COVID notwithstanding) with the most
aggressive DSM implementation categories of Education and Food Sales. Other influences on
UPC include differences in price sensitivity, sensitivity to business cycles and weather,
and degree and trends in automation. In addition, category UPC can vary when a customer’s
total use increases to the point where it must, by tariff rules, migrate to an industrial (Rate 19)
category. Tariff migration occurs at the boundary of Schedule 9P (large primary commercial)
and Schedule 19 (large industrial). Note that the forecast models aggregate the energy use of
these two schedules to mitigate this influence.
The commercial-sales forecast equations consider several varying factors, as informed by the
regression models, and vary depending on the category. Typical variables include corporate
earnings; government spending; wholesale/retail trade; HDD (wintertime); CDD (summertime);
specific industry growth characteristics and outlook; service-area demographics such as
households, employment, small business conditions; the real price of electricity; and energy
efficiency adoption.

0
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Class Sales Forecasts
Page 26 2021 Integrated Resource Plan—Appendix A
Industrial
The industrial category is comprised of Idaho Power’s large power service (Schedule 19)
customers requiring monthly metered demands between 1,000 kilowatts (kW) and 20,000 kW.
The category name “Industrial” is reflective of load requirements and not necessarily indicative
of the industrial nature of the customers’ business.
In 1980, Idaho Power had about 112 industrial customers, which represented about 12% of
Idaho Power’s system sales. By December 2020, the number of industrial customers had risen
to 123, representing approximately 17% of system sales. As mentioned earlier in the
commercial discussion, customer counts in this tariff class are impacted by migration to and
from the commercial class as dictated by the tariff rules. However, customer count growth is
primarily illustrative of the positive economic conditions in the service area. Customers with
load greater than Schedule 19 ranges are known as special contract customers and are
addressed in the Additional Firm Load section of this document.
In the anticipated forecast, industrial load grows from 295 aMW in 2021 to 397 aMW in 2040,
an average annual growth rate of 1.6% (Table 9). To a large degree, industrial load variability is
not associated with weather conditions as is the case with residential, commercial, and
irrigation; therefore, the forecasts in the 70th- and 90th-percentile weather scenarios are
identical to the anticipated industrial load scenario. The industrial load forecast is pictured in
Figure 15.
Table 9. Industrial load growth (aMW)
Growth 2021 2025 2030 2040
Annual Growth Rate
2021–2040
Anticipated Case .................................................................... 295 332 351 397 1.6%

Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 27

Figure 15. Forecast industrial load (aMW)
As discussed previously, the load growth variability is impacted by both economic,
non-weather factors, and the impacts of DSM. In developing the forecast, customer-specific
DSM implementation is isolated as DSM varies significantly by customer, and the actual energy
use is adjusted to remove the impacts of DSM to optimize the causal influence of non-DSM
causal variables. The history and forecast of DSM are provided by the DSM specialists within
Idaho Power. The economic and other independent variables for the regression models are
provided by third-party data providers and internally derived time-series for Idaho Power’s
service area.
Figure 16 illustrates the 2020 share of each of the categories within the Rate 19 customers.
By far, the largest share of electricity was consumed by the food manufacturing sector (38%),
followed by dairy (18%) and construction-related (7%). The categorization scheme includes a
range of service-providing industrial building types (assembly, lodging, mercantile, warehouse,
office, education, and health care). These provide the basis for capturing, modeling,
and forecasting the shifting economic landscape that influences industrial category
electricity sales.
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Class Sales Forecasts
Page 28 2021 Integrated Resource Plan—Appendix A
Figure 16. Industrial electricity consumption by industry group (based on 2020 sales)
The regression models and associated explanatory variables resulting from the categorization
establish the relationship between historical electricity sales and variables such as,
corporate earnings, economics, price, technological, demographic, and other influences in the
form of estimated coefficients from the industry group regression models applied to the
appropriate forecasts of independent time series of energy use. From this output, the history
and forecast of previously excluded DSM is subtracted. Figure 17 shows the general forecasting
methodology used for both the commercial and industrial sectors.

Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 29
Figure 17. Commercial and industrial general sales forecast methodology
Irrigation
The irrigation category is comprised of agricultural irrigation service customers. Service under
this schedule is applicable to power and energy supplied to agricultural-use customers at one
point-of-delivery for operating water pumping or water-delivery systems to irrigate agricultural
crops or pasturage.
The anticipated irrigation load is forecast to increase slowly from 225 aMW in 2021 to
250 aMW in 2040, an average annual compound growth rate of 0.6%. In the 70th-percentile
scenario, irrigation load is projected to be 241 aMW in 2021 and 266 aMW in 2040.
The anticipated, 70th-percentile, and 90th-percentile scenarios forecast slower growth than the
system in irrigation load from 2021 to 2040. The individual irrigation load forecasts are
summarized in Table 10 and illustrated in Figure 18.
Table 10. Irrigation load growth (aMW)
Growth 2021 2025 2030 2040
Annual Growth Rate
2021–2040
90th Percentile ....................................................................... 261 265 270 286 0.5%
70th Percentile ....................................................................... 241 244 250 266 0.5%
Anticipated Case .................................................................... 225 229 234 250 0.6%

Utility Data
IPCCommercial
and
Industrial
CommManuModel
Comm Large Services
IPCCommercialSales Forecast
CommServices Model
Comm LargeManu
Weather Data
IndustrialManu Model
IndustrialServices Model
UniqueIndustrialModels
IPC
IndustrialSales Forecast
IPC
Aggregate C/I
Sales
Forecast
Architecture = EconometricTraining Start = early 1990-2000Dependent Variable = Annual Sales
Economic Data
“Bolts”

Class Sales Forecasts
Page 30 2021 Integrated Resource Plan—Appendix A

Figure 18. Forecast irrigation load (aMW)
The annual average loads in Table 10 and Figure 18 are calculated using the 8,760 hours in a
typical year. In the highly seasonal irrigation sector, over 97% of the annual energy is billed
during the six months from May through October, and nearly half of the annual energy is billed
in just two months, July and August. During the summer, hourly irrigation loads can constitute
nearly 900 MW. In a normal July, irrigation pumping accounts for roughly 25% of the energy
consumed during the hour of the annual system peak and nearly 30% of the energy consumed
during July for general business sales. The forecasted increase of sales is due to the increased
customer count from the conversion of flood/furrow irrigation to sprinkler irrigation,
primarily related to farmers trying to reduce labor costs. Additionally, the trend toward more
water intensive crops—primarily alfalfa and corn—due to growth in the dairy industry,
explains most of the increased energy consumption in recent years.
The 2021 IRP irrigation sales forecast model considers several factors affecting electricity sales
to the irrigation class, including temperature; precipitation; Palmer Z Index (calculated by the
National Ocean and Atmospheric Administration [NOAA] from a combination of precipitation,
temperature, and soil moisture data); Moody’s Producer Price Index: Prices Received by
Farmers, All Farm Products; and annual maximum irrigation customer counts.
Actual irrigation electricity sales have grown from the 1970 level of 816,000 MWh to a peak
amount of 2,097,000 MWh in 2013. In 1977, irrigation sales reached a maximum proportion of
20% of Idaho Power system sales. In 2020, the irrigation proportion of system sales was 13%
due to the much higher relative growth in other customer classes.
0
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Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 31
Regarding customer growth, in 1980, Idaho Power had about 10,850 active irrigation accounts.
By 2020, the number of active irrigation accounts had increased to 20,800 and is projected to
be nearly 25,800 at the end of the planning period in 2040.
As with other sectors, average use per customer is an important consideration. Since 1988,
Idaho Power has experienced growth in the number of irrigation customers but slow growth in
total electricity sales (weather-adjusted) to this sector. The number of customers has increased
because customers are converting previously furrow-irrigated land to sprinkler irrigated land.
The conversion rate is slow and the kWh use per customer is substantially lower than the
average existing Idaho Power irrigation customer. This is because water for sprinkler
conversions is drawn from canals and not pumped from deep groundwater wells. In future
forecasts, factors related to the conjunctive management of ground and surface water and the
possible litigation associated with the resolution will require consideration. Depending on the
resolution of these issues, irrigation sales may be impacted.
Additional Firm Load
The additional firm load category consists of Idaho Power’s largest customers. Idaho Power’s
tariff requires the company serve requests for electric service greater than 20 MW under a
special-contract schedule negotiated between Idaho Power and each large-power customer.
The contract and tariff schedule are approved by the appropriate regulatory body. A special
contract allows customer-specific, cost-of-service analysis and unique operating characteristics
to be accounted for in the agreement.
Individual energy and peak-demand forecasts are developed with for special-contract
customers, including Micron Technology, Inc.; Simplot Fertilizer Company (Simplot Fertilizer);
the Idaho National Laboratory (INL); and any anticipated special contract customer(s) at the
time. These special-contract customers comprise the forecast category labeled additional
firm load.
In the anticipated forecast, additional firm load is expected to increase from 108 aMW in 2021
to 345 aMW in 2040, an average growth rate of 6.3% per year over the planning period
(Table 11). The additional firm load energy and demand forecasts in the 70th- and
90th-percentile scenarios are identical to the anticipated-load growth scenario. The scenario of
projected additional firm load is illustrated in Figure 19.
Table 11. Additional firm load growth (aMW)
Growth 2021 2025 2030 2040 Annual Growth Rate 2021–2040
Anticipated Case .................................................................... 108 195 345 345 6.3%

Class Sales Forecasts
Page 32 2021 Integrated Resource Plan—Appendix A

Figure 19. Forecast additional firm load (aMW)
Micron Technology
Micron Technology represents Idaho Power’s largest electric load for an individual customer
and employs approximately 5,000–6,000 workers in the Boise MSA. The company operates its
research and development fabrication facility in Boise and performs a variety of other activities,
including product design and support, quality assurance, systems integration and related
manufacturing, and corporate and general services. Micron Technology’s electricity use is a
function of the market demand for their products.
Simplot Fertilizer
This facility named the Don Plant is located just outside Pocatello, Idaho. The Don Plant is one
of four fertilizer manufacturing plants in the J.R. Simplot Company’s Agribusiness Group.
Vital to fertilizer production at the Don Plant is phosphate ore mined at Simplot’s Smoky
Canyon mine on the Idaho/Wyoming border. According to industry standards, the Don Plant is
rated as one of the most cost-efficient fertilizer producers in North America. In total,
J.R. Simplot Company employs 2,000–3,000 workers throughout its Idaho locations.
Idaho National Laboratory
Idaho National Laboratory (INL) is one of the United States Department of Energy’s (DOE)
national laboratories and is the nation’s lead laboratory for nuclear energy research,
development, and demonstration. The DOE, in partnership with its contractors, is focused on
performing research and development in energy programs and national defense. Much of the
0
50
100
150
200
250
300
350
400
1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
Actual Anticipated Case

Class Sales Forecasts
2021 Integrated Resource Plan—Appendix A Page 33
work to achieve this mission at INL is performed in government-owned and leased buildings on
the Research and Education Campus (REC) in Idaho Falls, Idaho, and on the INL site,
located approximately 50 miles west of Idaho Falls. INL is recognized as a critical economic
driver and important asset to the state of Idaho and is the fifth largest employer in the state of
Idaho with employees estimated at 4,225 workers.
Anticipated Large-Load Growth
Idaho Power’s anticipated load forecast includes new large-load growth. This growth reflects
industrial customers that have made a sufficient and significant binding investment and/or
interest indicating a commitment of the highest probability of locating in Idaho Power’s
service area.

Additional Considerations
Page 34 2021 Integrated Resource Plan—Appendix A
ADDITIONAL CONSIDERATIONS
Several influential components and their associated impacts to the sales forecast are treated
differently in the forecasting and planning process. The following discussion touches on several
of those important topics.
Energy Efficiency
Energy efficiency (EE) influences on past and future load consist of utility programs,
statutory codes, and manufacturing standards for appliances, equipment, and building
materials that reduce energy consumption. As the influence of statutory codes and
manufacturing standards on customers has increased in importance relative to utility programs,
Idaho Power continues to modify its forecasting models to fully capture the impact.
Idaho Power works closely with its internal DSM program managers and utilizes the updated
potential study, most recently developed by Applied Energy Group (AEG). DSM guidance and
the achievable potential from AEG are used as a benchmark metric for validating forecast
model output.
For residential models, the physical unit flow of energy-efficient products is captured through
integrating regional energy efficient product-shipments data into the retail and wholesale
distribution channels. The source for the shipments data is the Department of Energy (DOE)
and is consistent with DOE’s National Energy Model (NEM). This data is first refined by Itron for
utility-specific applications. This data captures energy-efficient installations regardless of the
source (e.g., programs, standards, and codes).
The DOE/Itron data is recognized in the industry as well-specified for the homogeneous
residential sector, however, although DOE data is available for the commercial sector,
Idaho Power’s test-modeling of the data indicates that the regional data does not provide
sufficient segmentation to recognize the heterogeneous differences between the Idaho
regional micro-economic composition and the mountain region economy. As discussed in the
previous section on forecast methodology within the commercial class, Idaho Power segments
the commercial customers by economic and energy profiles and incorporates historical energy
efficiency adoption into billed sales. Thus, the energy efficiency is directly modeled into the
forecast model energy variable and the forecast is adjusted in conformance with the DSM and
AEG potential study forecast to recognize energy efficiency. DOE data is not available for the
industrial sector.
The weather and agricultural volatility of the billed sales for the irrigation sector is not
well-suited for modeling energy efficiency impacts. Idaho Power monitors energy efficiency
implementation in history and forecasts from internal and external sources (DSM staff and
presently AEG). The trend of historical implementation (imbedded in the historical usage data)

Additional Considerations
2021 Integrated Resource Plan—Appendix A Page 35
provides a guideline for evaluating the model forecast output relative to expected DSM and
codes and standards.
As discussed above, Idaho Power continuously evaluates the models for adequately capturing
the impacts of energy efficiency and implements improvements when indicated. With input
from DSM program managers and AEG’s knowledge base, Idaho Power retains a high
confidence in the representation of the impacts of energy efficiency in the forecast.
A more detailed description of DSM can be found in the main IRP document under the Energy
Efficiency Section. Additionally, the company publishes a dedicated DSM annual report
submitted to the regulatory agencies.
On-Site Generation
In recent years, the number of customers transitioning from standard to net-metering service
(Schedules 6, 8, and 84) has risen dramatically, especially for residential customers. While the
current population of on-site generation customers is over 1% of the population of retail
customers, recent adoption of solar is relatively strong for our service area.
The installation of generating and storage equipment at customer sites will cause the demand
for electricity delivered by Idaho Power to be reshaped throughout the year. It is important to
measure the overall and future impact on the sales forecast. Therefore, this year’s long-term
sales forecast was adjusted downward to reflect the impact of the increase in the number
customers with on-site generation, specifically solar, connecting to our system.
Schedules 6, 8, and 84 (net-metering) customer billing histories were compared to billing
histories prior to said customer becoming a net-metering customer. The resulting average
monthly impact per customer (in kWh) was then multiplied by forecasts of the Schedule 6,
8, and 84 residential, commercial, and irrigation customer counts to estimate the future energy
impact on the sales forecast. The forecast of net metering customers serves as a function of
historical trends and current policy considerations.
The resulting forecast of net-metering customers multiplied by the estimated use-per-customer
sales impact per customer results in a monthly downward adjustment to the sales forecast for
each class. At the end of the forecast period, 2040, the annual residential sales forecast
reduction was about 65 aMW, the commercial reduction was 3 aMW, and the irrigation
reduction was 6 aMW.
Electric Vehicles
The load forecast includes an update of the impact of plug-in electric vehicles (PEV) on system
load to reflect the future impact of this relatively new and evolving source of energy use.
While electric vehicle (EV) consumer adoption rates in Idaho Power’s service area remain
relatively low, with continued technological advancement, limiting attributes of vehicle range

Additional Considerations
Page 36 2021 Integrated Resource Plan—Appendix A
and refueling time continue to improve the competitiveness of these vehicles to
non-electric models.
As the market grows, historical adoption data builds to provide a foundation for forecasting
adoption rates and for the models to evolve. Idaho Power receives detailed registration data
from Idaho Transportation Department (ITD). The data provides county-level registration which
provides a basis for determining Idaho Power service-territory vehicle inventory.
However, at present, this data is only available for battery-only vehicles and data for hybrid
engine-battery vehicles was not available for this forecast update. Other data sources for
monitoring the outlook for PEV adoption includes the United States Department of Energy,
R.L. Polk, and Moody’s Analytics.
Recent registration data shows a strong correlation between vehicles transferred into the
service territory and growth of residential in-migration from states with higher PEV share
(e.g., California and Washington). Idaho Power subsequently developed a regression model to
test the relationship utilizing migration, population, and Moody’s car registration forecasts.
The model results confirm the correlation, and the forecast outlook conforms well with the
generalized model utilizing DOE data.
The evolution of the PEV market shows that high adoption continues to be evident in warmer
climates, high-density and affluent population centers. The Idaho Power forecast for PEVs
shows that the service territory will continue to fall into the lower adoption ranges.
Idaho Power continues to monitor battery technology advancement, vehicle prices,
charging rates, and charging station availability which will serve to build the adoption rate in
the service territory.
Demand Response
Beginning with the 2009 IRP, the reduction in load associated with demand response programs
has been effectively treated as a supply side resource and accounted for in the load and
resource balance. Demand response program data, including operational targets for demand
reduction, program expenses, and cost-effective summaries are detailed in Appendix C—
Technical Appendix.
As supply-side resources, demand response program impacts are not incorporated into the
sales and load forecast. In the load and resource balance, the forecast of existing demand
response programs is subtracted from the peak-hour load forecast prior to accounting for
existing supply side resources. Likewise, the performance of new demand response programs is
accounted for prior to determining the need for additional supply-side resources.
However, because energy efficiency programs have an impact on peak demand reduction,
a component of peak hour load reduction is integrated into the sales and load forecast models.
This provides a consistent treatment of both types of programs, as energy efficiency programs

Additional Considerations
2021 Integrated Resource Plan—Appendix A Page 37
are considered in the sales and load forecast, while all demand response programs are included
in the load and resource balance.
A thorough description of each of the energy efficiency and demand response programs is
included in Appendix B—Demand-Side Management 2020 Annual Report.
Fuel Prices
Fuel prices, in combination with service-area demographic and economic drivers, impact long
term trends in electricity sales. Changes in relative fuel prices can also impact the future
demand for electricity. Class-level and economic-sector-level regression models were used to
identify the relationships between real historical electricity prices and their impact on historical
electricity sales. The estimated coefficients from these models were used as drivers in the
individual sales forecast models.
Short-term and long-term nominal electricity price increases are generated internally from
Idaho Power financial models. The nominal price estimates are adjusted for projected inflation
by applying the appropriate economic deflators to arrive at real fuel prices. The projected
average annual growth rates of fuel prices in nominal and real terms (adjusted for inflation)
are presented in Table 12. The growth rates shown are for residential fuel prices and can be
used as a proxy for fuel-price growth rates in the commercial, industrial, and irrigation sectors.
Table 12. Residential fuel-price escalation (2021–2040) (average annual percent change)
Nominal Real*
Electricity—2021 IRP .......................................................................... 1.0% -1.3%
Electricity—2019 IRP .......................................................................... 1.1% -1.1%
Natural Gas ........................................................................................ 2.2% 0.0%
* Adjusted for inflation

Figure 20 illustrates the average electricity price paid by Idaho Power’s residential customers
over the historical period 1985 to 2020 and over the forecast period 2021 to 2040.
Both nominal and real prices are shown. In the 2021 IRP, nominal electricity prices are expected
to climb to about 12.5 cents per kWh by the end of the forecast period in 2040. Real electricity
prices (inflation adjusted) are expected to decline over the forecast period at an average rate of
1.3% annually. In the 2019 IRP, nominal electricity prices were assumed to climb to about
14 cents per kWh by 2040, and real electricity prices (inflation adjusted) were expected to
decline over the forecast period at an average rate of 1.1% annually.
The electricity price forecast used to prepare the sales and load forecast in the 2021 IRP
reflected the additional plant investment and variable costs of integrating the resources
identified in the 2019 IRP preferred portfolio. When compared to the electricity price forecast
used to prepare the 2019 IRP sales and load forecast, the 2021 IRP price forecast yields lower

Additional Considerations
Page 38 2021 Integrated Resource Plan—Appendix A
future prices. The retail prices are mostly lower throughout the planning period which can
impact the sales forecast, a consequence of the inverse relationship between electricity prices
and electricity demand.
Figure 20. Forecast residential electricity prices (cents per kWh)
Electricity prices for Idaho Power customers increased significantly in 2001 and 2002, a direct
result of the western United States energy crisis of 2000 and 2001. Prior to 2001, Idaho Power’s
electricity prices were historically quite stable. From 1990 to 2000, nominal electricity prices
rose only 8% overall, an annual average compound growth rate of 0.8% annually. In contrast,
from 2000 to 2010, nominal electricity prices rose 63% overall, an annual average compound
growth rate of 4.2% annually. More recently, over the period 2010 to 2020, nominal electricity
prices rose 23% overall, an annual average compound growth rate of 1.8% annually.
Figure 21 illustrates the average natural gas price paid by Intermountain Gas Company’s
residential customers over the historical period 1985 to 2020 and forecast prices from 2020 to
2040. Natural gas prices remained stable and flat throughout the 1990s before moving sharply
higher in 2001. After spiking in 2001, natural gas prices moved downward for a couple of years
before moving sharply upward in 2004 through 2006. Since 2006, natural gas prices have
declined by 47%, compared to 2020. Nominal natural gas prices are initially expected to remain
relatively flat through 2022, drop in 2023, and then rise at a steady pace throughout the
remainder of the forecast period, increasing 70% by 2040, growing at an average rate of 2.2%
per year. Real natural gas prices (adjusted for inflation) are expected to increase over the same
period at an average rate of 0% annually.
0
2
4
6
8
10
12
14
16
18
20
1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
Nominal Real Nominal - 2021 IRP Real - 2021 IRP

Additional Considerations
2021 Integrated Resource Plan—Appendix A Page 39
Figure 21. Forecast residential natural gas prices (dollars per therm)
One consideration in determining the operating costs of space heating and water heating is fuel
cost, if future natural gas price increases outpace electricity price increases, heating with
electricity would become more advantageous when compared to that of natural gas.
S&P Global Platts provides the forecasts of long-term changes in nominal natural gas prices.
In the 2021 IRP price forecast, the long-term direction in real electricity prices (adjusted for
inflation) is downward and the long-term projection in real natural gas prices is downward in
the near term through 2023, with prices slowly rising throughout the forecast period after that.
Other Considerations
Since the residential, commercial, irrigation, and industrial sales forecasts provide a forecast of
sales as billed, it is necessary to adjust these billed sales to the proper time frame to reflect the
required generation needed in each calendar month. To determine calendar-month sales from
billed sales, the billed sales must first be converted from billed periods to calendar months to
synchronize them with the period in which load is generated. The calendar-month sales are
then converted to calendar-month average load by adding losses and dividing by the number of
hours in each month.
Loss factors are determined by Idaho Power’s Transmission Planning department. The annual
average energy loss coefficients are multiplied by the calendar-month load, yielding the system
load, including losses. A system loss study of 2012 was completed in May 2014. The results of
the study concluded that on average, the revised loss coefficients were lower than those
applied to generation forecasts developed prior to the 2015 IRP and were used in the
$0.00
$0.20
$0.40
$0.60
$0.80
$1.00
$1.20
$1.40
$1.60
$1.80
1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040
Nominal Forecast Nominal Actual Real Actual Real Forecast

Additional Considerations
Page 40 2021 Integrated Resource Plan—Appendix A
development of the 2021 IRP sales and load forecast. This resulted in a one-time permanent
reduction of nearly 20 aMW to the load forecast annually.
Hourly Load Forecast
As a result of stakeholder feedback and comments filed in the 2017 and 2019 IRPs, Idaho Power
has leveraged several years of advanced metering infrastructure (AMI) data to adopt a new
hourly load forecasting methodology to be used in the 2021 IRP. The use of AMI data expanded
its footprints at Idaho Power and is utilized to inform an hourly load forecast that conforms
with forecast methods mentioned throughout this document.
Historical IRP Methodology
Historically, Idaho Power has utilized metered system generation reads and weather data to
build a typical system load factor or hourly system shape based on a previous year, which was
then applied to the monthly load forecast for the IRP planning horizon. This methodology
produced a consistent system shape throughout the load forecast, but it lacked the significant
statistical footing of using individual hourly regressions rooted in AMI.
2021 IRP Methodology
In the time between IRP filings, Idaho Power began exploring potential methodology changes
regarding hourly load forecasting relative to what the company currently had in place.
While evaluating potential changes, the company believes it is prudent to maintain the integrity
of the historic long-term forecasting methodologies previously employed by Load Forecasting.
Based on the research, the company concluded that a new methodology could be developed
using a neural network. A neural network utilizes the stability of monthly sales data to calibrate
and ground the hourly data via monthly peak regressions. Further, the methodology employs
control and flexibility on the neural network while still leaning on its more robust
statistical underpinnings.
Enhancements to Hourly Load Forecasting
To begin the process, the company engaged in consultation with Itron Forecasting.
Together, Idaho Power and Itron designed the framework to introduce concepts of a neural
network model that utilized two non-linear nodes and was hinged on currently accepted load
forecasting processes. The result of this methodology brought statistical confidence of hourly
load modeling to the company while still conforming to the stability of the legacy methodology
of monthly sales forecasting.
An industry approach to weather responsiveness would be to utilize a linear model based on a
heating degree day or cooling degree day level of 65 degrees Fahrenheit (°F) (actual point may
differ by local utility weather characteristics). Utilities will also often use splines in regression

Additional Considerations
2021 Integrated Resource Plan—Appendix A Page 41
equations to define the weather function to reflect the change of slope as the average daily
temperature moves away from the 65°F mark and there is less weather responsiveness.
This methodology works very well by minimizing the potential impact of overfitting. Building on
this framework, Idaho Power uses a non-linear approach, wherein the derivative or local slope
of a curve is calculated at each instance along the weather responsiveness curve.
This responsiveness is captured in the neural network.
The neural network design adopted by Idaho Power outputs a single series of hourly energy
with only one hidden layer that contains two nodes (H1 and H2) representing the heating and
cooling effects along the sales curve. Each of the H1 and H2 nodes uses a logistic activation
function with a linear function applied to the output layer, where impacts of the calendar
(weekend, weekday, holidays, etc.) are captured.
A distinct model is developed for each hour of the year to capture the full spectrum of
temperature responsiveness. For each non-linear hourly model, an instantaneous derivative
value is calculated along the curve to obtain the relationship of energy sales to temperature.
A key initiative for Idaho Power when using a neural network framework is controllability of
calculations and reducing risk of overfitting of the tails of the distribution. This is achieved by
capturing the derivative value and using it in the hourly forecast using 5-degree gradation bins.
Further, by releasing the slopes in this fashion, it creates unique weighting schemes by hour
and facilitates the construction of lagged weather impact, weekends, and holidays. The result of
these hourly models is a transparent set of weather response functions.
At this point, a typical meteorological year is developed using a rolling 30 years of weather
history within the Idaho Power service territory. The company then uses an algorithm to rank
and average the daily temperature within a month from hottest to coldest, averaging the daily
temperature for each rank across years. The result is an appropriate representation of severe,
moderate, and mild daily temperatures for each month. The company then uses that ranked
and averaged typical weather by month and employs a transformation algorithm to reorder
days based on a typical weather pattern. Finally, a rotation algorithm is used to ensure that the
values over the forecast periods occur on the same day of the week throughout the forecast
period, removing the year-to-year variation in the hourly load shape based on where it lands on
the calendar of the given forecast year.
Hourly System Load Forecast Design
The output from the neural network is then joined with the abovementioned typical
meteorological year (TMY) to develop a near final hourly forecast. An important aspect of the
design was for the company to preserve the monthly sales and monthly peak forecast that has
been used historically. The newly developed methodology leverages a more statistically
confident approach for allocated sales by hour within the month. To maintain conformance

Additional Considerations
Page 42 2021 Integrated Resource Plan—Appendix A
with the historical methodology, the company applies a calibration algorithm to the hourly
forecast to both the monthly peak and energy sales within a month as produced by the legacy
linear forms the company operates. The output of hourly sales and subsequent monthly peaks,
as defined from the above-mentioned models, are adjusted such that the duration curve
receives minimal adjustment during or around the peak hour, and any required adjustment
grows larger as it moves out along the duration curve. This minimizes potential impacts of
creating large hour-to-hour swings.
The above process can be repeated for each major customer class to produce estimated
contributions to system peak by customer class as can be seen in Figure 22.

* Total includes impact from losses
Figure 22. Class Contribution to System Peak
Residential
37%
Residential
35%
Commercial/Industrial
28%
Commercial/Industrial
32%
Irrigation
19%
Irrigation
22%
Specials8%
Specials
3%
2040
2021
3,602
4,700

Contract Off-System Load
2021 Integrated Resource Plan—Appendix A Page 43
CONTRACT OFF-SYSTEM LOAD
The contract off-system category represents long-term contracts to supply firm energy to
off-system customers. Long-term contracts are contracts effective during the forecast period
lasting for more than one year. Currently, there are no long-term contracts.
The historical consumption for the contract off-system load category was considerable in the
early 1990s; however, after 1995, off-system loads declined through 2005. As intended,
the off-system contracts and their corresponding energy requirements expired as
Idaho Power’s surplus energy diminished due to retail load growth. In the future, Idaho Power
may enter additional long-term contracts to supply firm energy to off-system customers if
surplus energy is available.

Appendix A1
Page 44 2021 Integrated Resource Plan—Appendix A
Appendix A1. Historical and Projected Sales and Load
Company System Load (excluding Astaris)
Historical Company System Sales and Load, 1980–2020 (weather adjusted)
Year
Billed Sales
(thousands of MWh) Percent Change Average Load (aMW)
1980 7,866 974
1981 8,181 4.0% 1,014
1982 7,822 -4.4% 973
1983 8,034 2.7% 998
1984 8,120 1.1% 1,006
1985 8,262 1.7% 1,026
1986 8,346 1.0% 1,037
1987 8,489 1.7% 1,055
1988 8,832 4.0% 1,094
1989 9,203 4.2% 1,143
1990 9,575 4.0% 1,189
1991 9,749 1.8% 1,210
1992 9,973 2.3% 1,235
1993 10,268 3.0% 1,276
1994 10,676 4.0% 1,326
1995 11,140 4.4% 1,381
1996 11,479 3.0% 1,421
1997 11,770 2.5% 1,460
1998 12,261 4.2% 1,519
1999 12,558 2.4% 1,557
2000 12,951 3.1% 1,604
2001 13,089 1.1% 1,618
2002 12,791 -2.3% 1,587
2003 13,131 2.7% 1,627
2004 13,362 1.8% 1,655
2005 13,721 2.7% 1,705
2006 13,994 2.0% 1,735
2007 14,386 2.8% 1,785
2008 14,490 0.7% 1,789
2009 14,010 -3.3% 1,738
2010 13,876 -1.0% 1,720
2011 13,908 0.2% 1,724
2012 14,093 1.3% 1,742

Appendix A1
2021 Integrated Resource Plan—Appendix A Page 45
Year Billed Sales (thousands of MWh) Percent Change Average Load (aMW)
2013 14,101 0.1% 1,756
2014 14,283 1.3% 1,768
2015 14,131 -1.1% 1,753
2016 14,300 1.2% 1,773
2017 14,422 0.8% 1,788
2018 14,605 1.3% 1,813
2019 14,762 1.1% 1,834
2020 14,928 1.1% 1,856

Company System Load
Projected Company System Sales and Load, 2021–2040
Year
Billed Sales (thousands
of MWh) Percent Change Average Load (aMW)
2021 15,283 2.4% 1,895
2022 15,528 1.6% 1,926
2023 15,845 2.0% 1,965
2024 16,175 2.1% 2,008
2025 16,338 1.0% 2,082
2026 16,587 1.5% 2,154
2027 16,761 1.1% 2,223
2028 16,889 0.8% 2,269
2029 16,996 0.6% 2,289
2030 17,117 0.7% 2,304
2031 17,199 0.5% 2,314
2032 17,314 0.7% 2,322
2033 17,396 0.5% 2,338
2034 17,535 0.8% 2,356
2035 17,686 0.9% 2,375
2036 17,848 0.9% 2,389
2037 18,030 1.0% 2,418
2038 18,231 1.1% 2,442
2039 18,404 0.9% 2,464
2040 18,604 1.1% 2,482

Appendix A1
Page 46 2021 Integrated Resource Plan—Appendix A
Residential Load
Historical Residential Sales and Load, 1980–2020 (weather adjusted)
Year
Average
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average
Load (aMW)
1980 209,629 14,771 3,096 353
1981 213,579 1.9% 14,748 3,150 1.7% 355
1982 216,696 1.5% 13,562 2,939 -6.7% 337
1983 219,849 1.5% 14,321 3,149 7.1% 358
1984 222,695 1.3% 14,031 3,125 -0.8% 355
1985 225,185 1.1% 13,867 3,123 -0.1% 356
1986 227,081 0.8% 14,028 3,186 2.0% 365
1987 228,868 0.8% 13,970 3,197 0.4% 366
1988 230,771 0.8% 14,232 3,284 2.7% 375
1989 233,370 1.1% 14,217 3,318 1.0% 380
1990 238,117 2.0% 14,261 3,396 2.3% 388
1991 243,207 2.1% 14,373 3,496 2.9% 401
1992 249,767 2.7% 14,104 3,523 0.8% 401
1993 258,271 3.4% 14,088 3,638 3.3% 417
1994 267,854 3.7% 14,008 3,752 3.1% 429
1995 277,131 3.5% 14,024 3,887 3.6% 444
1996 286,227 3.3% 13,794 3,948 1.6% 451
1997 294,674 3.0% 13,728 4,045 2.5% 462
1998 303,300 2.9% 13,791 4,183 3.4% 478
1999 312,901 3.2% 13,654 4,272 2.1% 488
2000 322,402 3.0% 13,442 4,334 1.4% 494
2001 331,009 2.7% 13,210 4,373 0.9% 498
2002 339,764 2.6% 12,708 4,318 -1.3% 495
2003 349,219 2.8% 12,817 4,476 3.7% 511
2004 360,462 3.2% 12,755 4,598 2.7% 525
2005 373,602 3.6% 12,752 4,764 3.6% 547
2006 387,707 3.8% 12,992 5,037 5.7% 576
2007 397,286 2.5% 13,024 5,174 2.7% 591
2008 402,520 1.3% 12,942 5,209 0.7% 593
2009 405,144 0.7% 12,786 5,180 -0.6% 590
2010 407,551 0.6% 12,524 5,104 -1.5% 583
2011 409,786 0.5% 12,485 5,116 0.2% 583
2012 413,610 0.9% 12,403 5,130 0.3% 583
2013 418,892 1.3% 12,069 5,055 -1.5% 581
2014 425,036 1.5% 11,996 5,099 0.9% 579

Appendix A1
2021 Integrated Resource Plan—Appendix A Page 47
Year Average Customers Percent Change kWh per Customer Billed Sales (thousands of MWh) Percent Change Average Load (aMW)
2015 432,275 1.7% 11,691 5,054 -0.9% 577
2016 440,362 1.9% 11,642 5,127 1.4% 585
2017 448,800 1.9% 11,552 5,184 1.1% 592
2018 459,128 2.3% 11,385 5,227 0.8% 596
2019 471,298 2.7% 11,287 5,320 1.8% 609
2020 484,433 2.8% 11,450 5,547 4.3% 637

Projected Residential Sales and Load, 2021–2040
Year Average Customers Percent Change kWh per Customer Billed Sales (thousands of MWh) Percent Change Average Load (aMW)
2021 499,559 3.1% 11,281 5,636 1.6% 644
2022 513,957 2.9% 11,110 5,710 1.3% 652
2023 527,572 2.6% 10,941 5,772 1.1% 660
2024 540,764 2.5% 10,789 5,834 1.1% 665
2025 553,746 2.4% 10,591 5,865 0.5% 670
2026 566,899 2.4% 10,405 5,898 0.6% 674
2027 579,731 2.3% 10,231 5,931 0.6% 678
2028 591,914 2.1% 10,082 5,968 0.6% 680
2029 603,243 1.9% 9,945 5,999 0.5% 685
2030 613,993 1.8% 9,803 6,019 0.3% 687
2031 624,544 1.7% 9,669 6,039 0.3% 690
2032 634,909 1.7% 9,534 6,053 0.2% 689
2033 645,083 1.6% 9,396 6,062 0.1% 692
2034 655,094 1.6% 9,319 6,105 0.7% 697
2035 665,028 1.5% 9,274 6,168 1.0% 705
2036 674,971 1.5% 9,237 6,235 1.1% 710
2037 684,927 1.5% 9,209 6,308 1.2% 721
2038 694,856 1.4% 9,180 6,379 1.1% 729
2039 704,784 1.4% 9,154 6,451 1.1% 737
2040 714,731 1.4% 9,129 6,524 1.1% 743

Appendix A1
Page 48 2021 Integrated Resource Plan—Appendix A
Commercial Load
Historical Commercial Sales and Load, 1980–2020 (weather adjusted)
Year
Average
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average
Load (aMW)
1980 28,797 54,184 1,560 178
1981 29,567 2.7% 54,326 1,606 2.9% 184
1982 30,167 2.0% 54,147 1,633 1.7% 186
1983 30,776 2.0% 52,643 1,620 -0.8% 185
1984 31,554 2.5% 53,824 1,698 4.8% 194
1985 32,418 2.7% 54,495 1,767 4.0% 202
1986 33,208 2.4% 54,027 1,794 1.6% 205
1987 33,975 2.3% 53,710 1,825 1.7% 209
1988 34,723 2.2% 54,567 1,895 3.8% 216
1989 35,638 2.6% 55,654 1,983 4.7% 227
1990 36,785 3.2% 56,088 2,063 4.0% 236
1991 37,922 3.1% 56,385 2,138 3.6% 245
1992 39,022 2.9% 56,761 2,215 3.6% 253
1993 40,047 2.6% 58,693 2,350 6.1% 269
1994 41,629 4.0% 58,612 2,440 3.8% 280
1995 43,165 3.7% 59,035 2,548 4.4% 292
1996 44,995 4.2% 62,399 2,808 10.2% 321
1997 46,819 4.1% 62,490 2,926 4.2% 334
1998 48,404 3.4% 62,989 3,049 4.2% 349
1999 49,430 2.1% 64,468 3,187 4.5% 364
2000 50,117 1.4% 66,281 3,322 4.2% 380
2001 51,501 2.8% 67,783 3,491 5.1% 398
2002 52,915 2.7% 65,108 3,445 -1.3% 394
2003 54,194 2.4% 64,529 3,497 1.5% 399
2004 55,577 2.6% 64,280 3,573 2.2% 408
2005 57,145 2.8% 63,785 3,645 2.0% 417
2006 59,050 3.3% 63,731 3,763 3.2% 430
2007 61,640 4.4% 63,533 3,916 4.1% 448
2008 63,492 3.0% 62,458 3,966 1.3% 450
2009 64,151 1.0% 59,998 3,849 -2.9% 440
2010 64,421 0.4% 59,098 3,807 -1.1% 434
2011 64,921 0.8% 58,806 3,818 0.3% 436
2012 65,599 1.0% 59,128 3,879 1.6% 441
2013 66,357 1.2% 58,834 3,904 0.7% 448
2014 67,113 1.1% 59,173 3,971 1.7% 452

Appendix A1
2021 Integrated Resource Plan—Appendix A Page 49
Year Average Customers Percent Change kWh per Customer Billed Sales (thousands of MWh) Percent Change Average Load (aMW)
2015 68,000 1.3% 58,772 3,996 0.6% 457
2016 68,883 1.3% 58,226 4,011 0.4% 457
2017 69,850 1.4% 58,031 4,053 1.1% 462
2018 71,104 1.8% 57,942 4,120 1.6% 471
2019 72,332 1.7% 57,126 4,132 0.3% 472
2020 73,703 1.9% 54,687 4,031 -2.5% 460

Projected Commercial Sales and Load, 2021–2040
Year Average Customers Percent Change kWh per Customer Billed Sales (thousands of MWh) Percent Change Average Load (aMW)
2021 75,289 2.2% 55,179 4,154 3.1% 475
2022 76,982 2.2% 54,790 4,218 1.5% 482
2023 78,717 2.3% 54,161 4,263 1.1% 487
2024 80,420 2.2% 53,893 4,334 1.7% 494
2025 82,123 2.1% 53,161 4,366 0.7% 499
2026 83,847 2.1% 52,530 4,404 0.9% 503
2027 85,591 2.1% 51,550 4,412 0.2% 504
2028 87,323 2.0% 50,905 4,445 0.7% 506
2029 89,008 1.9% 50,313 4,478 0.7% 512
2030 90,638 1.8% 49,915 4,524 1.0% 517
2031 92,235 1.8% 49,301 4,547 0.5% 519
2032 93,818 1.7% 49,004 4,597 1.1% 524
2033 95,394 1.7% 48,471 4,624 0.6% 528
2034 96,961 1.6% 48,127 4,666 0.9% 533
2035 98,524 1.6% 47,622 4,692 0.5% 536
2036 100,086 1.6% 47,267 4,731 0.8% 539
2037 101,652 1.6% 47,034 4,781 1.1% 546
2038 103,220 1.5% 46,896 4,841 1.2% 553
2039 104,791 1.5% 46,674 4,891 1.0% 559
2040 106,365 1.5% 46,508 4,947 1.1% 564

Appendix A1
Page 50 2021 Integrated Resource Plan—Appendix A
Irrigation Load
Historical Irrigation Sales and Load, 1980–2020 (weather adjusted)
Year
Maximum Active
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average Load
(aMW)
1980 10,854 160,699 1,744 199
1981 11,248 3.6% 168,950 1,900 9.0% 217
1982 11,312 0.6% 152,063 1,720 -9.5% 197
1983 11,133 -1.6% 147,885 1,646 -4.3% 188
1984 11,375 2.2% 136,181 1,549 -5.9% 176
1985 11,576 1.8% 133,372 1,544 -0.3% 176
1986 11,308 -2.3% 135,042 1,527 -1.1% 174
1987 11,254 -0.5% 132,422 1,490 -2.4% 170
1988 11,378 1.1% 138,605 1,577 5.8% 180
1989 11,957 5.1% 136,898 1,637 3.8% 187
1990 12,340 3.2% 148,190 1,829 11.7% 209
1991 12,484 1.2% 139,041 1,736 -5.1% 198
1992 12,809 2.6% 139,340 1,785 2.8% 203
1993 13,078 2.1% 132,733 1,736 -2.7% 198
1994 13,559 3.7% 132,365 1,795 3.4% 205
1995 13,679 0.9% 132,064 1,807 0.7% 206
1996 14,074 2.9% 127,939 1,801 -0.3% 205
1997 14,383 2.2% 118,804 1,709 -5.1% 195
1998 14,695 2.2% 120,611 1,772 3.7% 202
1999 14,912 1.5% 121,861 1,817 2.5% 207
2000 15,253 2.3% 128,582 1,961 7.9% 223
2001 15,522 1.8% 117,166 1,819 -7.3% 208
2002 15,840 2.0% 109,361 1,732 -4.7% 198
2003 16,020 1.1% 112,556 1,803 4.1% 206
2004 16,297 1.7% 108,438 1,767 -2.0% 201
2005 16,936 3.9% 105,450 1,786 1.1% 204
2006 17,062 0.7% 98,468 1,680 -5.9% 192
2007 17,001 -0.4% 105,169 1,788 6.4% 204
2008 17,428 2.5% 108,589 1,892 5.8% 215
2009 17,708 1.6% 101,150 1,791 -5.4% 204
2010 17,846 0.8% 102,345 1,826 2.0% 209

Appendix A1
2021 Integrated Resource Plan—Appendix A Page 51
Year
Maximum
Active
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average Load
(aMW)
2011 18,292 2.5% 100,456 1,838 0.6% 210
2012 18,675 2.1% 104,483 1,951 6.2% 222
2013 19,017 1.8% 103,133 1,961 0.5% 224
2014 19,328 1.6% 103,920 2,009 2.4% 229
2015 19,756 2.2% 95,126 1,879 -6.4% 215
2016 20,042 1.4% 96,382 1,932 2.8% 220
2017 20,246 1.0% 90,552 1,833 -5.1% 209
2018 20,459 1.1% 92,940 1,901 3.7% 217
2019 20,566 0.5% 92,107 1,894 -0.4% 216
2020 20,804 1.2% 95,385 1,984 4.8% 226

Appendix A1
Page 52 2021 Integrated Resource Plan—Appendix A
Projected Irrigation Sales and Load, 2021–2040
Year
Maximum
Active
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average Load
(aMW)
2021 21,063 1.2% 93,540 1,970 -0.7% 225
2022 21,290 1.1% 92,318 1,965 -0.2% 224
2023 21,538 1.2% 92,090 1,983 0.9% 226
2024 21,786 1.2% 91,540 1,994 0.5% 227
2025 22,035 1.1% 90,887 2,003 0.4% 229
2026 22,283 1.1% 90,320 2,013 0.5% 230
2027 22,531 1.1% 89,780 2,023 0.5% 231
2028 22,782 1.1% 89,216 2,033 0.5% 231
2029 23,028 1.1% 88,648 2,041 0.4% 233
2030 23,278 1.1% 88,097 2,051 0.5% 234
2031 23,527 1.1% 87,552 2,060 0.4% 235
2032 23,774 1.0% 87,170 2,072 0.6% 236
2033 24,024 1.1% 86,879 2,087 0.7% 238
2034 24,274 1.0% 86,599 2,102 0.7% 240
2035 24,522 1.0% 86,333 2,117 0.7% 242
2036 24,770 1.0% 86,082 2,132 0.7% 243
2037 25,020 1.0% 85,852 2,148 0.7% 245
2038 25,267 1.0% 85,634 2,164 0.7% 247
2039 25,515 1.0% 85,457 2,180 0.8% 249
2040 25,763 1.0% 85,311 2,198 0.8% 250

Industrial Load
Historical Industrial Sales and Load, 1980–2020 (not weather adjusted)
Year
Average
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average Load
(aMW)
1980 112 9,894,706 1,106 125
1981 118 5.7% 9,718,723 1,148 3.9% 132
1982 122 3.5% 9,504,283 1,162 1.2% 133
1983 122 -0.3% 9,797,522 1,194 2.7% 138
1984 124 1.5% 10,369,789 1,282 7.4% 147
1985 125 1.2% 10,844,888 1,357 5.9% 155
1986 129 2.7% 10,550,145 1,357 -0.1% 155

Appendix A1
2021 Integrated Resource Plan—Appendix A Page 53
Year
Average
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average Load
(aMW)
1987 134 4.1% 11,006,455 1,474 8.7% 169
1988 133 -1.0% 11,660,183 1,546 4.9% 177
1989 132 -0.6% 12,091,482 1,594 3.1% 183
1990 132 0.2% 12,584,200 1,662 4.3% 191
1991 135 2.5% 12,699,665 1,719 3.4% 196
1992 140 3.4% 12,650,945 1,770 3.0% 203
1993 141 0.5% 13,179,585 1,854 4.7% 212
1994 143 1.7% 13,616,608 1,948 5.1% 223
1995 120 -15.9% 16,793,437 2,021 3.7% 230
1996 103 -14.4% 18,774,093 1,934 -4.3% 221
1997 106 2.7% 19,309,504 2,042 5.6% 235
1998 111 4.6% 19,378,734 2,145 5.0% 244
1999 108 -2.3% 19,985,029 2,160 0.7% 247
2000 107 -0.8% 20,433,299 2,191 1.5% 250
2001 111 3.5% 20,618,361 2,289 4.4% 260
2002 111 -0.1% 19,441,876 2,156 -5.8% 246
2003 112 1.0% 19,950,866 2,234 3.6% 255
2004 117 4.3% 19,417,310 2,269 1.5% 259
2005 126 7.9% 18,645,220 2,351 3.6% 270
2006 127 1.0% 18,255,385 2,325 -1.1% 265
2007 123 -3.6% 19,275,551 2,366 1.8% 270
2008 119 -3.1% 19,412,391 2,308 -2.4% 261
2009 124 4.0% 17,987,570 2,224 -3.6% 254
2010 121 -2.0% 18,404,875 2,232 0.3% 254
2011 120 -1.1% 18,597,050 2,230 -0.1% 254
2012 115 -4.2% 19,757,921 2,271 1.8% 258
2013 114 -0.7% 20,281,837 2,314 1.9% 265
2014 113 -0.7% 20,863,653 2,363 2.1% 271
2015 116 2.8% 20,271,082 2,360 -0.1% 269
2016 118 1.4% 19,993,955 2,361 0.0% 270
2017 117 -1.1% 20,996,425 2,453 3.9% 280
2018 115 -1.6% 21,274,929 2,447 -0.3% 280
2019 124 8.0% 20,288,866 2,521 3.0% 288

Appendix A1
Page 54 2021 Integrated Resource Plan—Appendix A
Year
Average
Customers
Percent
Change
kWh per
Customer
Billed Sales
(thousands of MWh)
Percent
Change
Average Load
(aMW)
2020 124 -0.3% 19,912,671 2,466 -2.2% 283

Appendix A1
2021 Integrated Resource Plan—Appendix A Page 55
Projected Industrial Sales and Load, 2021–2040
Year
Average
Customers
Percent
Change
kWh per
Customer
Billed Sales (thousands
of MWh)
Percent
Change
Average Load
(aMW)
2021 124 -0.2% 20,879,623 2,580 4.6% 295
2022 123 -0.5% 21,326,834 2,623 1.7% 300
2023 123 0.0% 22,198,824 2,730 4.1% 313
2024 125 1.6% 22,532,633 2,817 3.2% 321
2025 126 0.8% 22,993,784 2,897 2.9% 332
2026 126 0.0% 23,539,107 2,966 2.4% 339
2027 126 0.0% 23,746,821 2,992 0.9% 342
2028 129 2.4% 23,388,087 3,017 0.8% 344
2029 130 0.8% 23,420,860 3,045 0.9% 348
2030 130 0.0% 23,653,746 3,075 1.0% 351
2031 130 0.0% 23,868,001 3,103 0.9% 355
2032 132 1.5% 23,787,633 3,140 1.2% 358
2033 133 0.8% 23,849,695 3,172 1.0% 362
2034 133 0.0% 24,135,122 3,210 1.2% 367
2035 133 0.0% 24,409,273 3,246 1.1% 371
2036 135 1.5% 24,355,460 3,288 1.3% 375
2037 135 0.0% 24,705,719 3,335 1.4% 381
2038 135 0.0% 25,098,479 3,388 1.6% 387
2039 135 0.0% 25,405,447 3,430 1.2% 392
2040 137 1.5% 25,425,088 3,483 1.6% 397

Appendix A1
Page 56 2021 Integrated Resource Plan—Appendix A
Additional Firm Sales and Load
Historical Additional Firm Sales and Load, 1980–2020
Year
Billed Sales
(thousands of MWh) Percent Change Average Load (aMW)
1980 360 41
1981 376 4.6% 43
1982 367 -2.4% 42
1983 425 15.7% 49
1984 466 9.7% 53
1985 471 1.1% 54
1986 482 2.4% 55
1987 502 4.2% 57
1988 530 5.6% 60
1989 671 26.5% 77
1990 625 -6.9% 71
1991 661 5.8% 75
1992 680 2.9% 77
1993 689 1.3% 79
1994 740 7.5% 85
1995 878 18.6% 100
1996 989 12.6% 113
1997 1,048 6.0% 120
1998 1,113 6.2% 127
1999 1,121 0.8% 128
2000 1,143 1.9% 130
2001 1,118 -2.1% 128
2002 1,139 1.9% 130
2003 1,120 -1.7% 128
2004 1,156 3.3% 132
2005 1,175 1.6% 134
2006 1,189 1.2% 136
2007 1,141 -4.0% 130
2008 1,114 -2.4% 127
2009 965 -13.4% 110
2010 907 -6.0% 103
2011 906 0.0% 103
2012 862 -4.8% 98
2013 867 0.5% 99
2014 841 -2.9% 96

Appendix A1
2021 Integrated Resource Plan—Appendix A Page 57
Year Billed Sales (thousands of MWh) Percent Change Average Load (aMW)
2015 842 0.1% 96
2016 870 3.3% 99
2017 897 3.1% 102
2018 910 1.4% 104
2019 895 -1.7% 102
2020 900 0.6% 103
*Includes Micron Technology, Simplot Fertilizer, INL, Hoku Materials, City of Weiser, and Raft River Rural Electric Cooperative, Inc.

Projected Additional Firm Sales and Load, 2021–2040
Year
Billed Sales
(thousands of MWh)
Percent Change Average Load (aMW)
2021 943 4.7% 108
2022 1,019 8.1% 116
2023 1,104 8.4% 126
2024 1,288 16.7% 147
2025 1,706 32.4% 195
2026 2,163 26.8% 247
2027 2,668 23.3% 305
2028 2,996 12.3% 341
2029 3,010 0.4% 344
2030 3,025 0.5% 345
2031 3,027 0.1% 346
2032 3,032 0.2% 345
2033 3,028 -0.1% 346
2034 3,029 0.0% 346
2035 3,040 0.4% 347
2036 3,043 0.1% 346
2037 3,035 -0.3% 346
2038 3,036 0.0% 347
2039 3,028 -0.3% 346
2040 3,032 0.1% 345
*Includes Micron Technology, Simplot Fertilizer, the INL, and any anticipated special contract customers