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

Zahedi, Rafi; Sheinberg, Rachel; Narayana Gowda, Shashank; SedghiSigarchi, Kourosh; Gadh, Rajit

doi:10.3390/wevj16060318

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

by

Rafi Zahedi

^1,*

,

Rachel Sheinberg

¹,

Shashank Narayana Gowda

¹

,

Kourosh SedghiSigarchi

² and

Rajit Gadh

¹

Smart Grid Energy Research Center, University of California, Los Angeles, Los Angeles, CA 90095, USA

²

Electrical and Computer Engineering Department, California State University, Northridge, Los Angeles, CA 91330, USA

^*

Author to whom correspondence should be addressed.

World Electr. Veh. J. 2025, 16(6), 318; https://doi.org/10.3390/wevj16060318

Submission received: 4 May 2025 / Revised: 31 May 2025 / Accepted: 5 June 2025 / Published: 8 June 2025

(This article belongs to the Special Issue Fast-Charging Station for Electric Vehicles: Challenges and Issues)

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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.

Keywords: electric vehicle; heavy-duty electric vehicle; multi-period sizing; optimization; uncertainty modeling; charging station

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MDPI and ACS Style

Zahedi, R.; Sheinberg, R.; Narayana Gowda, S.; SedghiSigarchi, K.; Gadh, R. A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty. World Electr. Veh. J. 2025, 16, 318. https://doi.org/10.3390/wevj16060318

AMA Style

Zahedi R, Sheinberg R, Narayana Gowda S, SedghiSigarchi K, Gadh R. A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty. World Electric Vehicle Journal. 2025; 16(6):318. https://doi.org/10.3390/wevj16060318

Chicago/Turabian Style

Zahedi, Rafi, Rachel Sheinberg, Shashank Narayana Gowda, Kourosh SedghiSigarchi, and Rajit Gadh. 2025. "A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty" World Electric Vehicle Journal 16, no. 6: 318. https://doi.org/10.3390/wevj16060318

APA Style

Zahedi, R., Sheinberg, R., Narayana Gowda, S., SedghiSigarchi, K., & Gadh, R. (2025). A Framework for Optimal Sizing of Heavy-Duty Electric Vehicle Charging Stations Considering Uncertainty. World Electric Vehicle Journal, 16(6), 318. https://doi.org/10.3390/wevj16060318

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

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