Analyzing consumer acceptance of photovoltaics (PV) using fuzzy logic model

Consumer perception could play an important role in the adoption of renewable energy technologies. This study aims to explore the role of consumer acceptance and model its effect on residential photovoltaic (PV) adoption. A survey was conducted to understand consumer perceptions of the technology (perception variables), such as perceived cost, perceived maintenance requirement, and environmental concern. To further investigate the adoption potential of residential PV, this paper develops a fuzzy logic inference model to relate consumer perception variables (inputs to the model) to their purchasing probability (output from the model). This model is tested in a case study of residential PV adoption using data from a survey of homeowners in Arizona, United States. The quantitative results of the model demonstrate the role of each perception variable in the consumer acceptance of PV. Public has tended to emphasize on the role of cost reduction in promoting the adoption of residential PV. The results of this study show that other issues such as maintenance requirement and environmental concern are also important. Published by Elsevier Ltd.