A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty

The adoption of heavy-duty electric vehicles (HDEVs) is key to achieving transportation decarbonization. A major component of this transition is the need for new supporting infrastructure: electric charging stations (CSs). HDEV CSs must be planned considering charging requirements, economic constraints, the rollout plan for HDEVs, and local utility grid conditions. Together, these considerations highly differentiate HDEV CS planning from light-duty CS planning. This paper addresses the challenges of HDEV CS planning by presenting a framework for determining the optimal sizing of multiple HDEV CSs using a multi-period expansion model. The framework uses historical data from depots and applies a mixed-approach optimization solver to determine the optimal sizes of two types of CSs: one that relies entirely on power generated by a PV system with local battery storage, and another that relies entirely on utility grid power supply. A two-layer uncertainty model is proposed to account for variations in PV power generation, HDEV arrival/departure times, and charger failures. The multi-period expansion strategy achieves up to a 78% reduction in total annual costs during the first deployment period, compared to fully expanded CSs.

Authors

Institutions

Publication Details

Journal
World Electric Vehicle Journal
Published
2025-06-08
DOI
https://doi.org/10.3390/wevj16060318
Citations
3
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
2.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty

Rafi Zahedi, Rajit Gadh, Kourosh Sedghisigarchi, Shashank Narayana Gowda et al.
3 citations
World Electric Vehicle Journal
Electric Vehicles and Infrastructure
2.19
article

A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty

Rafi Zahedi, Rajit Gadh, Kourosh Sedghisigarchi, Shashank Narayana Gowda, Rachel Sheinberg
article en
3 citations

Abstract

The adoption of heavy-duty electric vehicles (HDEVs) is key to achieving transportation decarbonization. A major component of this transition is the need for new supporting infrastructure: electric charging stations (CSs). HDEV CSs must be planned considering charging requirements, economic constraints, the rollout plan for HDEVs, and local utility grid conditions. Together, these considerations highly differentiate HDEV CS planning from light-duty CS planning. This paper addresses the challenges of HDEV CS planning by presenting a framework for determining the optimal sizing of multiple HDEV CSs using a multi-period expansion model. The framework uses historical data from depots and applies a mixed-approach optimization solver to determine the optimal sizes of two types of CSs: one that relies entirely on power generated by a PV system with local battery storage, and another that relies entirely on utility grid power supply. A two-layer uncertainty model is proposed to account for variations in PV power generation, HDEV arrival/departure times, and charger failures. The multi-period expansion strategy achieves up to a 78% reduction in total annual costs during the first deployment period, compared to fully expanded CSs.

World Electric Vehicle JournalVol. 16(6)
California State University, Northridge (US), University of California, Los Angeles (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 12%
Electric Vehicles and Infrastructure
2.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty — Rafi Zahedi, Rajit Gadh, et al. · World Electric Vehicle Journal (2025) | TGRS Research Map | TGRS