Panel: Evidence on the Dynamics and Impacts of Distributed Solar Energy: Policies, Innovation, and Electricity Markets
(Natural Resource, Energy, and Environmental Policy)

Thursday, November 8, 2018: 1:45 PM-3:15 PM
Jackson - Mezz Level (Marriott Wardman Park)

*Names in bold indicate Presenter

Panel Chairs:  John Helveston, George Washington University
Discussants:  Johannes Urpelainen, Johns Hopkins University and Elizabeth Baldwin, University of Arizona

Getting More of Something without Subsidizing It: Impact of Time-of-Use Electricity Pricing on Residential Solar Panel Adoption
Yueming (Lucy) Qiu, University of Maryland, College Park, Jing Liang, University of Maryland, Pengfei Liu, University of Connecticut and Bo Xing, Salt River Project

Consumption Changes Following Solar Adoption: Testing for a Solar Rebound
Ross C Beppler, Georgia Institute of Technology

Promoting distributed solar energy has been a key strategy used by policy makers to address the challenges of climate change and environmental pollution as well as to improve energy access. The technologies, market structures and policies related to distributed solar energy industry have been evolving rapidly. Challenges still exist for the diffusion of solar energy technologies. Hence, it is critical for policy makers to understand the involvement of various stakeholders and the tradeoffs they face in order to introduce timely, efficient, and effective improvements to policies and programs. The critical stakeholders involved include policy makers, manufacturers, installers, electric utilities, and consumers. The dynamics among these key stakeholders are complex: policies affect solar photovoltaic (PV) market structure and lead to different levels of PV prices and deployment; innovation and knowledge spillovers also affect PV installation prices; electricity rate structure directly influences consumers’ solar adoption decisions; solar adoption in turn affects electricity consumption. The four papers in this panel provide empirical evidence for such complex dynamics in the distributed solar industry. This panel is closely relevant to the conference theme of evidence for action. Each of the four papers collects valuable and unique datasets on distributed solar energy, measures the impacts of various types of policies, programs, innovations, and market structures related to solar energy, and provides valuable policy implications to enhance social welfare and to improve various dimensions of the solar energy industry. 

The first paper analyzes the impact of technology innovation and knowledge spillover on solar PV installation prices. The authors develop a new database of PV balance-of-system patents, matched with a dataset of small-scale PV installations in the U.S.. Regression results separate the effect of productivity improvement from the effect of technology innovation, examining the potential for further cost reduction of PV. The second paper explores how policies influence the market structures of the solar installation industry. Market structure has important implications for the price of solar panels. Using a rich dataset of installed residential PV systems, this paper provides empirical evidence that more favorable policy environments lead to less market concentration as indicated by more installers and more even distribution of market shares. The third paper (one of the authors is a practitioner from a utility company) examines the impact of electricity rate structure on solar panel adoption. The authors use a large residential appliance saturation survey and provide empirical evidence that time-of-use (TOU) pricing can increase residential solar panel adoption by 27%. The magnitude of TOU’s impact is equivalent to that of 85% of the current size of financial incentives, implying that TOU could act as a more cost-effective policy instrument to promote solar panel adoption than financial incentives. The last paper quantifies the impact of solar adoption on residential electricity consumption. Two rival hypotheses have opposite implications: a rebound effect, and a green signal. The author uses high frequency electricity consumption data to analyze both aggregate and time differentiated electricity use to examine demand changes and load shifting of solar adopters and test these rival hypotheses.