Simultaneous capacity configuration and scheduling optimization of an integrated electrical vehicle charging station with photovoltaic and battery energy storage system
Xiao-Jian Dong,
Jia-Ni Shen,
Cheng-Wu Liu,
Zi-Feng Ma and
Yi-Jun He
Energy, 2024, vol. 289, issue C
Abstract:
The implementation of an optimal power scheduling strategy is vital for the optimal design of the integrated electric vehicle (EV) charging station with photovoltaic (PV) and battery energy storage system (BESS). However, traditional design methods always neglect accurate PV power modeling and adopt overly simplistic EV charging strategies, which might result in suboptimal and infeasible designs. This study proposes a novel simultaneous capacity configuration and scheduling optimization model for PV/BESS integrated EV charging stations, which combines hybrid modeling for PV power prediction and optimal scheduling method for charging piles. The original model is then converted to a mixed integer linear programming problem by the Big-M method to greatly reduce the computational complexity. A typical scenario of commercial region is employed to demonstrate the effectiveness of the proposed approach. The results indicate that the approach could improve economic benefits by 15.67 % and reduce carbon emissions by 37.14 % compared with the entire grid-based mode. Besides, integrating the PV hybrid modeling method and optimal charging scheduling strategy could achieve superior capacity configurations and greatly improve the comprehensive performance of the system. It is thus illustrated that the approach could provide a promising solution for the optimal design and scheduling of PV/BESS integrated EV charging stations.
Keywords: Capacity configuration and scheduling; Simultaneous optimization; Electrical vehicle charging station; Photovoltaic; Battery energy storage system (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:289:y:2024:i:c:s0360544223033856
DOI: 10.1016/j.energy.2023.129991
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