Predicting Rooftop Photovoltaic Adoption In The Residential Consumers of PLN Using Agent-Based Modeling

Abstract

Indonesia has a massive solar energy potential of about 207 gigawatts in 2015, unfortunately, the utilization only 0.04 percent. In 2017, the rooftop photovoltaic (PV) in Indonesia has become a trend adopted by residential consumers. Increasing the adoption of rooftop PV is one of the strategies to reach the 23 percent renewable energy mix by 2025. Therefore, to predict the rooftop PV adoptions in the future, Agent-Based Modeling (ABM) is applied. The purpose of the model is to understand the impact of decision-making behavior for the adoption of rooftop PV at the household level on electricity utilization from PLN. The simulation results are divided into sensitivity analysis and scenario analysis.The analysis indicates that the factors inherent in consumer behavior such as the level of adoption to adopt new technologies, the number of neighbors who have installed rooftop PV, lifestyle and intensity of exposure to social media have influenced the rate of adoption. The simulation results of several sensitivity analyses show that the higher theability of households to adopt new technologies and increased the number of neighbors who have installed rooftop PV have an impact on the increasinglevel of adoption on rooftop PV in this community. Meanwhile, the results of the scenario analysis showed that decreasing the price of rooftop PV per year and increased government subsidies have an impact on the increasing adoption rate of rooftop PV.