Hydrogen Supply Chain Network Optimization for Supporting Urban Hydrogen Vehicle Infrastructure Development

Rahmad Anasrul; Bertha Maya Sopha

doi:10.38043/tiers.v6i1.6453

Authors

Rahmad Anasrul Universitas Gadjah Mada, Indonesia
Bertha Maya Sopha Universitas Gadjah Mada, Indonesia

DOI:

https://doi.org/10.38043/tiers.v6i1.6453

Keywords:

Gravity Model, Hydrogen Refueling Station, Hydrogen Supply Chain, Mixed-Integer Linear Programming, Urban Energy Transition

Abstract

This study addressed the rising concerns regarding greenhouse gas emissions and the depletion of fossil fuel resources by exploring hydrogen as a clean energy alternative. The Indonesian government established a national roadmap that prioritized the transportation sector as a starting point for hydrogen deployment. The objective of this research was to design and optimize a hydrogen supply chain network in Jakarta, a densely populated urban area considered strategic for early adoption. The study applied a two-stage approach. First, potential locations for Hydrogen Refueling Stations (HRS) were pre-selected based on spatial and demographic scoring using a modified gravity model. Then the second, the optimal placement of HRS and hydrogen suppliers was determined through a Mixed-Integer Linear Programming (MILP) method. The entire modeling and optimization process was implemented in Python, with MILP solved using the Gurobi optimizer. A total of 216 existing gas stations were assessed and grouped into five priority levels. The optimization was conducted for three planning periods: 2026-2030, 2031-2035, and 2036-2040. The results showed that integrating new HRS into existing infrastructure reduced land use and investment costs. Sensitivity analysis indicated that daily HRS capacity, hydrogen demand, and capital cost were the most influential factors. The study concluded that this integrated approach provides an efficient, flexible, and sustainable foundation for future hydrogen infrastructure development in urban regions.

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