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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1517011
This article is part of the Research Topic Distributed Learning, Optimization, and Control Methods for Future Power Grids, Volume II View all 18 articles

Bi-objective Collaborative Optimization of a Photovoltaic-Energy Storage EV Charging Station with Consideration of Storage Capacity Impacts

Provisionally accepted
Wei Guo Wei Guo 1*Shengbo Sun Shengbo Sun 1Kai Nan Kai Nan 1Peng Tao Peng Tao 1Kaibin Wu Kaibin Wu 2,3Zhiqiang Wang Zhiqiang Wang 4Huimin Wang Huimin Wang 4Mengmeng Yue Mengmeng Yue 2,3Xinlei Bai Xinlei Bai 1Jianyong Ding Jianyong Ding 1
  • 1 State Grid Hebei Electric Power co. ltd, Shijiazhuang, China
  • 2 State Grid Hubei Electric Power Co., Ltd., Wuhan, Hubei Province, China
  • 3 Nari Group Corporation State Grid Electric Power Research Institute, Nanjing, Liaoning Province, China
  • 4 Northeastern University, Shenyang, Liaoning Province, China

The final, formatted version of the article will be published soon.

    This paper presents a novel integrated Green Building Energy System (GBES) by integrating photovoltaic-energy storage electric vehicle charging station(PV-ES EVCS) and adjacent buildings into a unified system. In this system, the building load is treated as an uncontrollable load and primarily utilized to facilitate the consumption of surplus photovoltaic (PV) power generated by EVCS. First, a strategy for determining the maximum value of the energy storage system (ESS) capacity is presented. Subsequently, to coordinate the charging and discharging plans of ESS, and electric vehicles(EVs), a bi-objective optimization model was established focusing on GBES power purchase costs and the load peak-valley difference. The proposed GBES efficiently utilizes the integrated energy system comprising charging stations and adjacent buildings, maximizing the use of photovoltaic energy and external power grids during low-cost periods. In experiments, we compare the proposed optimized charging strategy with the unordered charging case, the simulation results demonstrate that the proposed method for coordinating ESS and EVs charging can respectively reduce the cost of purchased power by 33.2% and the peak-to-valley difference in load by 47.6%.

    Keywords: Green Building Energy System (GBES), Bi-objective optimization, Electric vehicle(EV), Photovoltaic(PV), Energy storage system(ESS)

    Received: 25 Oct 2024; Accepted: 26 Nov 2024.

    Copyright: © 2024 Guo, Sun, Nan, Tao, Wu, Wang, Wang, Yue, Bai and Ding. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Wei Guo, State Grid Hebei Electric Power co. ltd, Shijiazhuang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.