ESTIMATING ELECTRIC VEHICLE PUBLIC CHARGING DEMAND ACROSS DKI JAKARTA USING AGENT-BASED MODELING AND SIMULATION

• Main Author: Nabil Sateriano, Farrel
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/72985
• Institution: Institut Teknologi Bandung

This research was conducted to estimate the public charging demand for electric vehicles across DKI Jakarta. This research also added robustness to the estimation by identifying the effect of electric vehicle home charging access and drivers' risk attitude towards state-of-charge and public charging demand. The research is classified as applied, prescriptive research by using the agent-based modeling and simulation technique. The researcher first gathered assumptions that are used in the modeling through secondary sources. The researcher then went through the pre-simulation validation to assure that the model simplification was appropriate. Throughout building the model, the researcher enforced the unit-testing approach to avoid code writing overdo while assuring codes are running as expected. After the simulation results were acquired, the researcher conducted the post-simulation validation to check whether the findings complied with existing theories and concepts related to the research's scope. This research finds that public charging demand is mainly clustered in Central Jakarta, followed by South, North, West, and East Jakarta.This research also finds that electric vehicle home charging access is positively correlated to state-of-charge and negatively correlated to public charging demand. On the other hand, electric vehicle drivers' risk attitude is shown to be positively correlated to state-of-charge and public charging demand. These findings accentuated the importance of considering DKI Jakarta citizens' accessibility to home charging and risk attitude in driving electric vehicles in capturing public charging demand and developing charging infrastructure so that official authorities can formulate the appropriate decisions and policies to address electric vehicle charging demand.