Spatial Analysis of EV Charging Demand for Intercity Bus Transport in Thailand

Kongwee, Worawut; Achariyaviriya, Witsarut; Rinchumphu, Damrongsak; Suttakul, Pana; Achariyaviriya, Aree · 2025 · Crossref

DOI: 10.5194/isprs-annals-x-4-w7-2025-83-2025

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study addresses the critical gap in spatial planning for Battery Electric Bus (BEB) charging infrastructure along Thailand’s intercity bus corridors. While the Thai government promotes BEV adoption to reduce greenhouse gas emissions, current strategies lack a spatially informed approach for placing charging stations along long-haul routes. The research aims to estimate spatial charging demand and identify optimal infrastructure locations to support the transition from internal combustion engine buses to electric alternatives, ensuring operational feasibility given the limited range of BEBs. The methodology utilizes intercity bus route data from Thailand’s Department of Land Transport, comprising 628 routes categorized as long-haul national or regional inter-provincial connections. Since the original dataset lacked geographic coordinates, the authors derived route geometries by geocoding origin-destination pairs to administrative centroids and generating polyline paths via the Google Directions API. Potential charging points were interpolated along these routes at 250-kilometer intervals, reflecting the typical operational range of BEBs. To quantify demand, the study applied a grid-based model dividing Thailand into 10 × 10 kilometer cells. A Charging Demand Score (CDS) was calculated for each cell using an exponential decay function, which weighted the proximity of candidate charging points to the grid cell, thereby identifying areas with the highest relative need for infrastructure. The results reveal that high charging demand is concentrated along major intercity corridors in the northern, northeastern, and southern regions. In the north, provinces such as Nakhon Sawan and Uttaradit exhibit elevated CDS values due to their role as junctions on routes connecting Bangkok to northern provinces. In the northeast, Nakhon Ratchasima recorded the highest CDS among all provinces, with Saraburi also identified as a high-demand node. Southern demand is significant in Samut Prakan, Prachuap Khiri Khan, and Chumphon, which serve as critical links between central and southern Thailand. The analysis suggests that strategic placement in these high-demand areas is essential for maintaining route continuity, particularly on long-distance corridors like Bangkok–Chiang Mai. The study concludes that aligning infrastructure planning with vehicle capabilities and spatial travel patterns is vital for successful electrification. The proposed CDS framework provides a data-driven foundation for policymakers to prioritize charging station deployment. However, the authors note limitations, including the assumption of equal trip frequency across routes and the exclusion of constraints such as grid capacity, land availability, and economic feasibility. Future work should integrate these practical factors and operational data, such as service frequency and passenger load, to bridge the gap between theoretical demand modeling and real-world implementation.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• bus coach