Simulating EV Growth Scenarios in Jawa-Madura-Bali from 2024 to 2029: Balancing the Power Grid’s Supply and Demand

Abstract

This study provides a comprehensive simulation for understanding the influence of EV growth and its external factors on grid stability and offers insights into effective management strategies. To manage the growth of battery-based electric vehicles (BEVs) in Indonesia and mitigate their impact on the power grid’s supply–demand equilibrium, regulatory adjustments and subsidies can be implemented by the government. The Jawa-Madura-Bali (Jamali) electrical system, as the largest in Indonesia, is challenged with accommodating the rising number of vehicles. Following an analysis of Jamali’s electricity supply using data from the National Electricity Company (RUPTL), simulations are constructed to model the grid’s demand side. Input variables such as Jamali’s population, the numbers of internal combustion engine (ICE) and electric vehicles, initial charging times (ICT), slow and fast charging ratios, and BEV charge load curves are simulated. Scenario variables, including supply capacity growth rate, vehicle population growth rate, subsidy impact on EV attractiveness, ICT, and fast charging ratio, are subsequently simulated for the 2024–2029 period. Four key simulation outcomes are identified. The best-case scenario (scenario 1776) achieves the highest EV growth with minimal grid disruption, resulting in a 45.38% EV percentage in 2029 and requiring an annual allocation of 492 billion rupiah to match supply with demand. The worst-case scenario leads to a 23.12% EV percentage, necessitating 47,566 billion rupiah for EV subsidies in 2029. Additionally, the most and least probable scenarios based on the literature research are evaluated. This novel simulation and its results provide insights into EV growth’s impact on the grid’s balance in one presidential term from 2024 to 2029, aiding the government in planning regulations and subsidies effectively.

Keywords

• electric vehicle
• power grid
• supply demand balance
• electrical grid
• electricity demand simulation
• electric vehicle subsidy