Consumer Choice Model for Forecasting Demand and Designing Incentives for Solar Technology

Abstract

In this paper, we develop a model for the adoption of solar photovoltaic technology by residential consumers. In particular, we assume consumers purchase these solar panels according to a discrete choice model. The technology adoption process is reinforced by network externalities such as imitating customer behavior and cost improvements through learning-by-doing. Using this model, we develop a framework for policy makers to find optimal subsidies in order to achieve a desired adoption target with minimum cost for the system. We discuss the structure of the optimal subsidy policy and how the overall system cost changes with the adoption target. Furthermore, we validate the model through an empirical study of the German solar market, where we estimate the model parameters, generate adoption forecasts and demonstrate how to solve the policy design problem. We use this framework to show that the current policies in Germany are not efficient. In particular, our study suggests that their subsidies should be higher in the near future and the gradual phase-out of the subsidies should occur faster.

Keywords: solar incentives, photovoltaic, technology adoption, german solar market, choice model