DEVELOPMENT OF A BEHAVIOR-BASED ANALYSIS FRAMEWORK FOR PROMOTING RPV DEPLOYMENT IN SINGAPORE

Abstract

Residential Photovoltaic (RPV) systems are one type of building-integrated photovoltaics (BIPV) specialized for residential buildings. The deployment of RPV is slow, especially in Southeast Asian countries. To promote RPV deployment, this research aims to analyze the mechanism of RPV adoption, diffusion and policy design considering the consumers’ RPV adoption behaviors and after-adoption energy behaviors. An Artificial Intelligence (AI) assisted agent-based simulation framework is constructed to link behaviors among stakeholders in the process (household owners, policymakers). The proposed research framework links the individuals’ behaviors and RPV marketing performance in the network, enabling behavioral-based policies to promote RPV further. The proposed research framework successfully integrates technologies from multiple disciplines: combining behavior theory from psychology, policy evaluation method from social science, and the advanced simulation technology from information engineering. The methodology and findings can be easily extended to develop other renewable energy technologies (RETs) across the globe.