Coordinated Sizing of Transformer and Hybrid Energy Storage Systems for PV-Integrated Ultra-Fast EV Charging Stations Considering Battery Degradation

Ultra-fast charging stations can impose substantial short-term power fluctuations and high transformer capacity requirements on distribution networks. To address the coupled planning and operational challenges of such stations, this study proposes a planning-operation coordinated sizing framework for a photovoltaic-integrated ultra-fast charging station. Unlike many existing approaches that address transformer sizing, energy storage configuration, and battery degradation separately or only partially couple them, the proposed framework jointly determines transformer capacity, battery capacity, and supercapacitor capacity while incorporating battery cycling degradation into the long-term storage cost evaluation. Representative charging scenarios are extracted from historical charging-load data and used for capacity planning. At the planning level, the average daily comprehensive cost is minimized by coordinating transformer investment, hybrid energy storage investment, operating cost, and degradation-dependent battery lifetime. At the operation level, battery and supercapacitor dispatch is optimized considering both operating economy and grid-connected power fluctuation. The upper-level sizing problem is solved using quantum-behaved particle swarm optimization. Sobol-sequence initialization and a nonlinear contraction-expansion coefficient are adopted in the implementation to enhance the distribution of the initial population and adjust the search range during the iterative process. The lower-level mixed-integer linear programming problem is solved using Gurobi. In the studied commercial-area case, the proposed hybrid energy storage configuration reduces the transformer capacity from 326 kVA to 201 kVA. Compared with the no-storage scheme, total costs are reduced by 14.9% and 14.3%, while the absolute deviations of grid-connected power are reduced by 93.4% and 94.8% for the two representative days. Compared with battery-only storage, daily battery cycle counts are further reduced by 60.5% and 65.2%. The results demonstrate that the proposed coordinated sizing framework can simultaneously reduce infrastructure capacity requirements and operating costs, improve grid integration performance, and alleviate battery cycling degradation in PV-integrated ultra-fast charging stations.

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Publication Details

Journal
Electronics
Published
2026-11-02
DOI
https://doi.org/10.3390/electronics15215075
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Coordinated Sizing of Transformer and Hybrid Energy Storage Systems for PV-Integrated Ultra-Fast EV Charging Stations Considering Battery Degradation

Yong Shi, Yang Zhang, Yu Liu, Haiwei Wang et al.
Electronics
Power Systems and Renewable Energy
article

Coordinated Sizing of Transformer and Hybrid Energy Storage Systems for PV-Integrated Ultra-Fast EV Charging Stations Considering Battery Degradation

Yong Shi, Yang Zhang, Yu Liu, Haiwei Wang, Lu Chen, Hao Zhang
article en

Abstract

Ultra-fast charging stations can impose substantial short-term power fluctuations and high transformer capacity requirements on distribution networks. To address the coupled planning and operational challenges of such stations, this study proposes a planning-operation coordinated sizing framework for a photovoltaic-integrated ultra-fast charging station. Unlike many existing approaches that address transformer sizing, energy storage configuration, and battery degradation separately or only partially couple them, the proposed framework jointly determines transformer capacity, battery capacity, and supercapacitor capacity while incorporating battery cycling degradation into the long-term storage cost evaluation. Representative charging scenarios are extracted from historical charging-load data and used for capacity planning. At the planning level, the average daily comprehensive cost is minimized by coordinating transformer investment, hybrid energy storage investment, operating cost, and degradation-dependent battery lifetime. At the operation level, battery and supercapacitor dispatch is optimized considering both operating economy and grid-connected power fluctuation. The upper-level sizing problem is solved using quantum-behaved particle swarm optimization. Sobol-sequence initialization and a nonlinear contraction-expansion coefficient are adopted in the implementation to enhance the distribution of the initial population and adjust the search range during the iterative process. The lower-level mixed-integer linear programming problem is solved using Gurobi. In the studied commercial-area case, the proposed hybrid energy storage configuration reduces the transformer capacity from 326 kVA to 201 kVA. Compared with the no-storage scheme, total costs are reduced by 14.9% and 14.3%, while the absolute deviations of grid-connected power are reduced by 93.4% and 94.8% for the two representative days. Compared with battery-only storage, daily battery cycle counts are further reduced by 60.5% and 65.2%. The results demonstrate that the proposed coordinated sizing framework can simultaneously reduce infrastructure capacity requirements and operating costs, improve grid integration performance, and alleviate battery cycling degradation in PV-integrated ultra-fast charging stations.

ElectronicsVol. 15(21)
Hefei University of Technology (CN), State Grid Corporation of China (China) (CN)
Openalex Percentile: Top 26%
Power Systems and Renewable Energy
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