Short-Term Energy Outlook: 

Small-Scale Solar Forecasts

www.eia.gov

U.S. Department of Energy

Washington, DC 20585

Last updated: December 2023 
U.S. Energy Information Administration | STEO Small-Scale Solar Forecasts i

The U.S. Energy Information Administration (EIA), the statistical and analytical agency within the 

U.S. Department of Energy (DOE), prepared this report. By law, our data, analyses, and forecasts are 

independent of approval by any other officer or employee of the U.S. Government. The views in this 

report do not represent those of DOE or any other federal agencies.
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U.S. Energy Information Administration | STEO Small-Scale Solar Forecasts 1

Table of Contents

Table of Figures.............................................................................................................................................1

1. Introduction ..............................................................................................................................................2

2. Model Outputs..........................................................................................................................................3

3. Data Sources .............................................................................................................................................4

4. Regional Fixed Effects for Small-Scale Solar Generating Capacity Estimates...........................................5

4.1 Small-scale solar power generating capacity.....................................................................................5

4.2 Small-scale solar power generation...................................................................................................7

Table of Figures

Figure 1. U.S. small-scale solar power generating capacity and generation ................................................2

Figure 2. Forecast regions for small-scale solar generating capacity ...........................................................3

Figure 3. U.S. small-scale solar capacity (2014–2024)..................................................................................7
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1. Introduction

Small-scale solar photovoltaic (PV) systems either can be interconnected with local electric distribution 

lines and send excess power onto the grid (net-metering), or they can provide power on-site only. We 

define small-scale solar PV systems as smaller than 1 megawatt (MW)1in size, typically installed on the 

rooftops of residences or businesses. Small-scale solar PV systems also include ground-mounted or 

other types of commercial and industrial solar systems less than 1 MW. They are also referred to as 

distributed generation systems to distinguish them from electric generating units at centrally located 

power plants. 

We publish forecasts of small-scale solar PV electric generating capacity in the Short-Term Energy 

Outlook (STEO). STEO Table 7e shows small-scale solar PV capacity forecasts for residential, commercial, 

and industrial sectors. The estimates of U.S. electricity generation presented in STEO Table 7a show 

historical data and forecasts for small-scale solar generation by sector, as measured in billion 

kilowatthours. The renewable energy historical data and forecasts for generation and capacity are also 

accessible through the STEO custom table builder, our Microsoft Excel add-in, and the EIA Application 

Programming Interface (API). In addition, we have provided annual estimates of capacity and generation 

for distributed PV systems at the national level in the Annual Energy Outlook.

The small-scale solar PV component of the STEO model is designed to provide monthly forecasts of U.S. 

capacity for the residential sector and the non-residential (commercial and industrial) sectors. We use

sector-level econometric regression equations to develop the projections, based on historical data that 

we publish.

Figure 1. U.S. small-scale solar power generating capacity and generation 

1 STEO publications generally report generating capacity data for all energy sources in alternating current (AC) electricity terms. 

The purpose of this threshold is to include PV capacity and generation that is otherwise not collected on Form EIA-860 and 

Form EIA-923, which collects data from utility-scale electricity generation systems.
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2. Model Outputs

The model estimates the small-scale solar capacity in the STEO forecast data series for each U.S. region. 

It produces monthly capacity estimates for 11 total regions (comprising 4 regions and 7 states) and 3 

sectors (residential, commercial and industrial) and then adds the regional totals to obtain the United 

States small-scale solar capacity forecast. Some are individual states that have 2 gigawatts (GW) or more 

of installed sectoral capacity (as of the October 2023 Form EIA-861M, Monthly Electric Power Industry 

Report). The remaining states have less than 2 GW and are aggregated into four census regions

(Northeast, Midwest, South, West). The series below are estimated by month and are reported in STEO 

Table 7e. 

• Residential small-scale solar generating capacity estimates

• Commercial small-scale solar generating capacity estimates

• Industrial small-scale solar generating capacity estimates

Figure 2. Forecast regions for small-scale solar generating capacity

In 2023, more than one-third of the residential small-scale solar PV capacity in the United States was in 

California, followed by Arizona with 8%. California is not only the most populous state but also has a 

long history of policies and state characteristics that encourage distributed PV generation. Texas and 

Florida were in third place, with 7% of the installed residential small-scale solar capacity, and New York 

had 4%. The rest of the states had smaller individual shares of installed small-scale solar capacity and

were grouped in four regions to account for the remaining residential installed capacity. The Northeast 

region without New York had 13% of the installed residential small-scale solar capacity, followed by the 

West region without Arizona and California, with 12% of the small-scale solar capacity installations; the 

South without Florida and Texas, with 8%; and lastly the Midwest, with 5%. 

Data source: U.S. Energy Information Administration, Form EIA-861M surveys, May 2023

Note: The different colors in the map represent the small-scale solar generating capacity forecast regions. 

Individual states have 2 gigawatts or more of installed capacity as of the October 2023 EIA-861M.

 Midwest

 Northeast

 New York

South

New Jersey

Texas

West

Massachusetts

Arizona

California

Florida
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Small-scale solar systems can serve different purposes. Each electricity market in the United States 

accounts differently for distributed generation. Smaller power systems connected to the distribution 

network can supply power to the grid when needed. Some systems are unregistered with Regional 

Transmission Organizations (RTOs); these systems are typically rooftop solar systems owned by 

residential customers and smaller than 1 MW. Other systems, such as the ones that offer supplemental 

generation at business locations, can provide backup power and are dispatched by the resource owner.

When registered with the RTOs, they can contribute to electricity supply in the United States. 

Distributed registered systems reporting more than 1 MW of installed capacity on our Monthly Update 

to the Annual Electric Generator Report (Form EIA-860M) are included in the STEO electricity supply 

model.

Capacity factors are expressed as the ratio of the average power generated over a period compared 

with the maximum possible output. So, the number of times a power plant can run for a particular 

period is expressed as a percentage and is used to calculate the actual energy generated by a power 

plant. For example, actual energy generated in a plant (measured in megawatthours) is obtained by 

multiplying installed capacity (megawatts) by the time period (hours) by the capacity factor 

(percentage).

We use the aggregated U.S. capacity factors for utility-scale solar forecasts in the STEO electricity supply 

model to compute U.S. small-scale solar electricity generation. The series below are reported in STEO 

Table 7a. 

• Residential small-scale solar electric power generation

• Commercial small-scale solar electric power generation

• Industrial small-scale solar electric power generation

Small-scale solar capacity estimates are not included in the STEO electricity supply model. 

3. Data Sources

The historical values for small-scale solar generation and capacity in STEO are based on net metering 

and non-net-metering distributed data collected in our Annual Electric Power Industry Report (Form EIA861) and our Monthly Electric Power Industry Report (Form EIA-861M). Detailed state-level and regional 

data for both generation and capacity are available by month from Form EIA-861M. We have published 

capacity and generation estimates from small-scale solar installations since 2015. Starting in 2020, we

added Annual Electric Power Industry Report (Form EIA-861S) respondents to the estimates of smallscale solar. Our Form EIA-861S survey collects information about utilities with small annual sales not 

included in Form EIA-861.

Small-scale solar data are collected and estimated from net-metering and non-net-metering distributed 

PV data using formulas and adjustments described in the technical notes of the Electric Power Monthly 

(EPM). Owners of the small-scale net-metered systems can be reimbursed by electric utilities for 

supplying electricity to the grid. Since 2014, we have published historical small-scale solar generating 

capacity and power generation for various regional divisions in our EPM.
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Currently, STEO incorporates historical small-scale solar PV data from Form EIA-861M and forecasts 

monthly U.S. generation and capacity values through the end of the STEO forecast horizon (12–24 

months) for the residential, commercial, and industrial sectors. 

4. Regional Fixed Effects for Small-Scale Solar Generating Capacity 

Estimates

To estimate small-scale solar power capacity, we use fixed-effects panel data methods, which involve a 

mathematical transformation to remove the unobserved heterogeneous factors that vary across states 

prior to estimation. For example, the installation of solar panels varies with state-specific characteristics 

that are not observed in the data, such as different local policies incentivizing the use of residential solar 

electricity. Fixed-effects panel data methods work similarly to linear regressions and estimate a different 

monthly slope (average growth) for each state and economic sector.

4.1 Small-scale solar power generating capacity

The model’s econometric regression equations are structured using fixed-effects panel data structures, 

which are designed to use variables that differ across regions or states to account for unobserved or 

omitted factors that are constant over time. In this case, we are relying on state fixed effects, which 

account for differences in state characteristics, especially different policies that incentivize the growth in 

small-scale solar generation. The model also captures socioeconomic differences across states. 

U.S. electric generating capacity data are by month and are measured in megawatts for the residential, 

commercial, and industrial sectors. We estimate one regression model for each sector: residential and 

non-residential (commercial and industrial). Each model returns nine different growth or regional paths 

for each sector. The regional composition corresponds to seven states and four aggregated regions as 

documented above. Table 1 presents the residential historical small-scale generating capacity estimates,

as of October 2023. Except for California, most of the states have less than 25 GW of residential installed 

capacity.

The econometric models for generating capacity rely on the growth of the previous month’s capacity 

and other explanatory variables. Other covariates are included in the regression to account for 

exogenous variation within the regions, such as the households’ ability to purchase solar PV systems.

The explanatory variables in the residential capacity regression model include:

• The monthly counts of households in the state registered in the U.S. Census data, measured 

in thousands, and its forecast (S&P Market Intelligence)

• Historical data on personal income, measured in millions of dollars by state or region, and its 

monthly forecast (S&P Market Intelligence)
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Table 1. Small-scale solar electric generating capacity by region (megawatts)

Region Residential Non-residential

Midwest 1,721 1,441

Northeast (without Massachusetts, New Jersey, and New York) 2,428 1,550

 Massachusetts 1,159 1,457

 New Jersey 1,311 1,194

 New York 1,355 1,518

South (without Florida and Texas) 1,764 626

 Florida 2,012 200

 Texas 2,439 300

West (without Arizona and California) 3,583 961

 Arizona 2,031 354

 California 11,140 4,749

Data source: U.S. Energy Information Administration, Form EIA-861M, Monthly Electric Power Industry Report, 

October 2023

The U.S. non-residential capacity forecast follows a similar approach as the state fixed effects panel data 

model. We forecast the growth in commercial and industrial solar PV installation based on past 

growth—specifically, installed capacity in the previous month and three months prior. 

Explanatory variables are also included to approximate industrial and commercial economic activity: 

• Employment in the private sector (measured in thousands) and its forecast (S&P Market 

Intelligence)

• State populations (measured in thousands) and their forecasts (S&P Market Intelligence)

Other regression models are used to estimate the amount of small-scale solar PV capacity in the 

commercial sector and industrial sector based on the initial non-residential total. The commercial sector 

is represented in the model as a share of non-residential capacity that is calculated monthly based on 

the most recent historical data. Forecast capacity for the industrial sector is then calculated as the 

difference between the forecast non-residential and commercial sector capacities.
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Figure 3. U.S. small-scale solar capacity (2014–2024)

4.2 Small-scale solar power generation

We develop small-scale solar electric power generation forecasts by state or aggregated region. The 

estimates of electric power generation rely on the estimates of capacity. The capacity forecasts are then 

used in other econometric regression equations to produce forecasts of monthly electricity generation 

for the residential and nonresidential sectors. The small-scale solar electric power generation estimates 

are based on historical seasonal patterns in the utilization rate of small-scale solar PV capacity and 

capacity factors. 

All equations in the small-scale solar model are estimated using monthly data from January 2014 

through the most recent available month. We periodically re-estimate the coefficients in each equation 

to capture the effect of recent data. We re-evaluate the specification of regression models in the STEO

to reflect the current market and regulatory structure of the industry.