Site Selection and Capacity Determination of Electric Hydrogen Charging Integrated Station Based on Voronoi Diagram and Particle Swarm Algorithm

Xueqin Tian, Heng Yang (), Yangyang Ge and Tiejiang Yuan
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Xueqin Tian: China Electric Power Research Institute Co., Ltd., Haidian District, Beijing 100192, China
Heng Yang: School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China
Yangyang Ge: Electric Power Research Institute of State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China
Tiejiang Yuan: School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China

Energies, 2024, vol. 17, issue 2, 1-26

Abstract: In response to challenges in constructing charging and hydrogen refueling facilities during the transition from conventional fuel vehicles to electric and hydrogen fuel cell vehicles, this paper introduces an innovative method for siting and capacity determination of Electric Hydrogen Charging Integrated Stations (EHCIS). In emphasizing the calculation of vehicle charging and hydrogen refueling demands, the proposed approach employs the Voronoi diagram and the particle swarm algorithm. Initially, Origin–Destination (OD) pairs represent car starting and endpoints, portraying travel demands. Utilizing the traffic network model, Dijkstra’s algorithm determines the shortest path for new energy vehicles, with the Monte Carlo simulation obtaining electric hydrogen energy demands. Subsequently, the Voronoi diagram categorizes the service scope of EHCIS, determining the equipment capacity while considering charging and refueling capabilities. Furthermore, the Voronoi diagram is employed to delineate the EHCIS service scope, determine the equipment capacity, and consider distance constraints, enhancing the rationality of site and service scope divisions. Finally, a dynamic optimal current model framework based on second-order cone relaxation is established for distribution networks. This framework plans each element of the active distribution network, ensuring safe and stable operation upon connection to EHCIS. To minimize the total social cost of EHCIS and address the constraints related to charging equipment and hydrogen production, a siting and capacity model is developed and solved using a particle swarm algorithm. Simulation planning in Sioux Falls city and the IEEE33 network validates the effectiveness and feasibility of the proposed method, ensuring stable power grid operation while meeting automotive energy demands.

Keywords: electric vehicles; hydrogen fuel cell vehicles; site selection and fixed capacity; Voronoi diagram; electric hydrogen charging integrated station (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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