skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Forecasting residential solar photovoltaic deployment in California

Journal Article · · Technological Forecasting and Social Change
 [1];  [2];  [2]
  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)
+ Show Author Affiliations

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.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Energy Information Administration (EIA)
Grant/Contract Number:
AC36-08GO28308; DOOE1000
OSTI ID:
1347199
Alternate ID(s):
OSTI ID: 1397475
Report Number(s):
NREL/JA-6A20-67441
Journal Information:
Technological Forecasting and Social Change, Vol. 117, Issue C; ISSN 0040-1625
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (31)

A New Product Growth for Model Consumer Durables journal January 1969
Why the Bass Model Fits without Decision Variables journal August 1994
The Impact of Heterogeneity and Ill-Conditioning on Diffusion Model Parameter Estimates journal May 2002
Peer Effects in the Diffusion of Solar Photovoltaic Panels journal November 2012
The role of prices in models of innovation diffusion journal December 1998
The role of the complementary sector and its relationship with network formation and government policies in emerging sectors: The case of solar photovoltaics between 2001 and 2009 journal February 2014
Interactions of rooftop PV deployment with the capacity expansion of the bulk power system journal April 2016
Modeling photovoltaic diffusion: an analysis of geospatial datasets journal July 2014
Predicting the costs of photovoltaic solar modules in 2020 using experience curve models journal December 2013
Deconstructing Solar Photovoltaic Pricing journal July 2016
Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns journal February 2010
Problems in Predicting New Product Growth for Consumer Durables journal October 1980
Advertising and the Diffusion of New Products journal February 1983
Forecasting with Exponential Smoothing book January 2008
A Generalized Norton–Bass Model for Multigeneration Diffusion journal October 2012
Photovoltaic Degradation Rates-an Analytical Review: Photovoltaic degradation rates journal October 2011
Modelling and forecasting the diffusion of innovation – A 25-year review journal January 2006
Beyond the learning curve: factors influencing cost reductions in photovoltaics journal November 2006
Solar Community Organizations and active peer effects in the adoption of residential PV journal April 2014
A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products journal September 1987
Effective information channels for reducing costs of environmentally- friendly technologies: evidence from residential PV markets journal March 2013
Agent-based modeling of energy technology adoption: Empirical integration of social, behavioral, economic, and environmental factors journal August 2015
Diffusion of environmentally-friendly energy technologies: buy versus lease differences in residential PV markets journal February 2013
Overcoming barriers and uncertainties in the adoption of residential solar PV journal April 2016
Business model innovation for sustainable energy: German utilities and renewable energy journal November 2013
Dynamic Price Models for New-Product Planning journal June 1975
Determinants of spatio-temporal patterns of energy technology adoption: An agent-based modeling approach journal August 2015
Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance journal February 1982
Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models journal May 1986
A Meta-Analysis of Applications of Diffusion Models journal February 1990
Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test journal November 2004

Cited By (2)

Addressing integration challenges of high shares of residential solar photovoltaics with battery storage and smart policy designs journal June 2019
Addressing integration challenges of high shares of residential solar photovoltaics with battery storage and smart policy designs text January 2019

Similar Records

Related Subjects

14 SOLAR ENERGY
29 ENERGY PLANNING, POLICY, AND ECONOMY
solar PV
forecasting
diffusion models
policy impact
policies
California