Agent-Based simulation and data mining analysis for effect of purchase price in households’ solar energy adoption process

Abstract

For promotion of solar energy popularization, study on effect of purchase price can facilitate proper product decisions making. In this paper, an agent based model is built to simulate the households’ dynamic adoption process of solar energy. With varying purchase price, scenario analysis is taken to investigate the relevant market share changes. Random forest is used to measure the effect of purchase price by data collected from the model changes. The results show that impacts of purchase price differ with different types of energy using by households. By energy subsidy, product with higher purchase price can still attract market share of solar energy effectively. Thus, promotion strategies should be variable according to local using conditions of solar energy in residential consumer market.