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Title: Forecasting residential solar photovoltaic deployment in California

Abstract

Residential distributed photovoltaic (PV) deployment in the United States has experienced robust growth, and policy changes impacting the value of solar are likely to occur at the federal and state levels. To establish a credible baseline and evaluate impacts of potential new policies, this analysis employs multiple methods to forecast residential PV deployment in California, including a time-series forecasting model, a threshold heterogeneity diffusion model, a Bass diffusion model, and National Renewable Energy Laboratory's dSolar model. As a baseline, the residential PV market in California is modeled to peak in the early 2020s, with a peak annual installation of 1.5-2 GW across models. We then use the baseline results from the dSolar model and the threshold model to gauge the impact of the recent federal investment tax credit (ITC) extension, the newly approved California net energy metering (NEM) policy, and a hypothetical value-of-solar (VOS) compensation scheme. We find that the recent ITC extension may increase annual PV installations by 12%-18% (roughly 500 MW, MW) for the California residential sector in 2019-2020. The new NEM policy only has a negligible effect in California due to the relatively small new charges (< 100 MW in 2019-2020). Moreover, impacts of the VOS compensationmore » scheme (0.12 cents per kilowatt-hour) are larger, reducing annual PV adoption by 32% (or 900-1300 MW) in 2019-2020.« less

Authors:
 [1];  [2];  [2]
+ Show Author Affiliations
  1. Renmin Univ. of China, Beijing (China); National Renewable Energy Lab. (NREL), Golden, CO (United States); RUC National Academy of Development and Strategy, Beijing (China)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Energy Information Administration (EIA)
OSTI Identifier:
1347199
Alternate Identifier(s):
OSTI ID: 1397475
Report Number(s):
NREL/JA-6A20-67441
Journal ID: ISSN 0040-1625
Grant/Contract Number:  
AC36-08GO28308; DOOE1000
Resource Type:
Accepted Manuscript
Journal Name:
Technological Forecasting and Social Change
Additional Journal Information:
Journal Volume: 117; Journal Issue: C; Journal ID: ISSN 0040-1625
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; solar PV; forecasting; diffusion models; policy impact; policies; California

Citation Formats

Dong, Changgui, Sigrin, Benjamin, and Brinkman, Gregory. Forecasting residential solar photovoltaic deployment in California. United States: N. p., 2016. Web. doi:10.1016/j.techfore.2016.11.021.
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Dong, Changgui, Sigrin, Benjamin, & Brinkman, Gregory. Forecasting residential solar photovoltaic deployment in California. United States. https://doi.org/10.1016/j.techfore.2016.11.021
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Dong, Changgui, Sigrin, Benjamin, and Brinkman, Gregory. Tue . "Forecasting residential solar photovoltaic deployment in California". United States. https://doi.org/10.1016/j.techfore.2016.11.021. https://www.osti.gov/servlets/purl/1347199.
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@article{osti_1347199,
title = {Forecasting residential solar photovoltaic deployment in California},
author = {Dong, Changgui and Sigrin, Benjamin and Brinkman, Gregory},
abstractNote = {Residential distributed photovoltaic (PV) deployment in the United States has experienced robust growth, and policy changes impacting the value of solar are likely to occur at the federal and state levels. To establish a credible baseline and evaluate impacts of potential new policies, this analysis employs multiple methods to forecast residential PV deployment in California, including a time-series forecasting model, a threshold heterogeneity diffusion model, a Bass diffusion model, and National Renewable Energy Laboratory's dSolar model. As a baseline, the residential PV market in California is modeled to peak in the early 2020s, with a peak annual installation of 1.5-2 GW across models. We then use the baseline results from the dSolar model and the threshold model to gauge the impact of the recent federal investment tax credit (ITC) extension, the newly approved California net energy metering (NEM) policy, and a hypothetical value-of-solar (VOS) compensation scheme. We find that the recent ITC extension may increase annual PV installations by 12%-18% (roughly 500 MW, MW) for the California residential sector in 2019-2020. The new NEM policy only has a negligible effect in California due to the relatively small new charges (< 100 MW in 2019-2020). Moreover, impacts of the VOS compensation scheme (0.12 cents per kilowatt-hour) are larger, reducing annual PV adoption by 32% (or 900-1300 MW) in 2019-2020.},
doi = {10.1016/j.techfore.2016.11.021},
journal = {Technological Forecasting and Social Change},
number = C,
volume = 117,
place = {United States},
year = {Tue Dec 06 00:00:00 EST 2016},
month = {Tue Dec 06 00:00:00 EST 2016}
}
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https://doi.org/10.1016/j.techfore.2016.11.021
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    Works referencing / citing this record:

    Addressing integration challenges of high shares of residential solar photovoltaics with battery storage and smart policy designs
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    • Schwarz, Marius; Ossenbrink, Jan; Knoeri, Christof
    • Environmental Research Letters, Vol. 14, Issue 7
    • DOI: 10.1088/1748-9326/aaf934
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