Spatial Allocation Model for Vehicle Charging Infrastructure with case of Indonesia New Capital City

Galih Prasetya Dinanta, Nugraheni Setyaningrum, Laju Ghandarum, Abdul Wachid Syamroni, Akim Windaru, Danang Yogisworo, Asih Kurniasari

Abstract


Indonesia's new capital city, Ibu Kota Nusantara (IKN), was launched in 2022 to replace Jakarta as a modern, sustainable city where all operating vehicles must be electric (EVs). This study identifies optimal locations for electric vehicle charging stations (EVCS) in support of IKN's 100% electrified transport systems (ETS) target by 2045. Implementing EVs in IKN requires optimum infrastructure readiness, including adequate EVCS distribution; no prior study has simulated this for IKN. This study introduces Spatial Model Simulation (SMS), a novel framework combining an agent-based model (ABM) and Markov Chain Monte Carlo (MCMC). ABM simulates EV mobility behaviour, while MCMC handles EVCS allocation across the Kawasan Inti Pusat Pemerintahan (KIPP) zone. This combination provides a spatially intuitive planning tool for government and policymakers. Results show that at a minimum inter-station range of 250 m, 25 EVCS are optimally distributed within KIPP, achieving an 88% allocation efficiency. Increasing the minimum range to 750 m reduces the total number to 22 stations. Area type also significantly influences optimal location and allocation (LA); misplacement leads to inefficiencies in infrastructure costs and maintenance budgets. Open space is the primary candidate area for EVCS installation, followed by residential and public service zones. Simulated energy demand for 100 vehicles ranges between 1,700 – 2,000 kWh per daily operating cycle. These findings offer practical guidance for decision-makers planning sustainable transport infrastructure in newly developed capital cities. 


Keywords


Electric Vehicles, Charging Station Placement, Artificial Neural Network, Spatial Modeling, travel distance, point of connection.

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v16i2.15358.g9221

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