A model for residential adoption of photovoltaic systems
Due to the growth in the number of residential photo voltaic (PV) adoptions in the past five years, there is a need in the electricity industry for a widely-accessible model that predicts the adoption of PV based on different business and policy decisions. We analyze historical adoption patterns and find that monetary savings is the most important factor in the adoption of PV, superseding all socioeconomic factors. On the basis of the findings from our data analysis, we created an application available on Google App Engine (GAE), that allows researchers, policymakers and regulators to study the complex relationship between PV adoption, grid sustainability and utility economics. This application allows users to experiment with a variety of scenarios including different tier structures, subsidies and customer demographics. We showcase the type of analyses that are possible with this application by using it to study the impact of different policies regarding tier structures, fixed charges and PV prices.
© 2015 IEEE. The authors would like to thank Prof. Steven Low, Prof. John Ledyard and Neil Fromer of Caltech and Andre Ramirez of SCE for helpful input. This work was supported by grants from Southern California Edison.