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Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System

Author

Listed:
  • Chao Ma

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China)

  • Sen Dong

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China)

  • Jijian Lian

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China)

  • Xiulan Pang

    (State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, China
    Huanghe Hydropower Development Co., Ltd., Xining 810008, China)

Abstract

Hybrid energy storage systems (HESS) are an effective way to improve the output stability for a large-scale photovoltaic (PV) power generation systems. This paper presents a sizing method for HESS-equipped large-scale centralized PV power stations. The method consists of two parts: determining the power capacity by a statistical method considering the effects of multiple weather conditions and calculating the optimal energy capacity by employing a mathematical model. The method fully considers the characteristics of PV output and multiple kinds of energy storage combinations. Additionally, a pre-storage strategy that can further improve stability of output is proposed. All of the above methods were verified through a case study application to an 850 MW centralized PV power station in the upstream of the Yellow river. The optimal hybrid energy storage combination and its optimization results were obtained by this method. The results show that the optimal capacity configuration can significantly improve the stability of PV output and the pre-storage strategy can further improve the target output satisfaction rate by 8.28%.

Suggested Citation

  • Chao Ma & Sen Dong & Jijian Lian & Xiulan Pang, 2019. "Multi-Objective Sizing of Hybrid Energy Storage System for Large-Scale Photovoltaic Power Generation System," Sustainability, MDPI, vol. 11(19), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5441-:d:272538
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    Cited by:

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    3. Hongyang He & Zhigang Lu & Xiaoqiang Guo & Changli Shi & Dongqiang Jia & Chao Chen & Josep M. Guerrero, 2022. "Optimized Control Strategy for Photovoltaic Hydrogen Generation System with Particle Swarm Algorithm," Energies, MDPI, vol. 15(4), pages 1-17, February.
    4. Ruonan Hu & Wei Wang & Zhe Chen & Xuezhi Wu & Long Jing & Wei Ma & Guohong Zeng, 2020. "Coordinated Voltage Regulation Methods in Active Distribution Networks with Soft Open Points," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    5. Yi Yan & Xuerui Wang & Ke Li & Xiaopeng Kang & Weizheng Kong & Hongcai Dai, 2022. "Tri-Level Integrated Optimization Design Method of a CCHP Microgrid with Composite Energy Storage," Sustainability, MDPI, vol. 14(9), pages 1-29, April.
    6. Yeon-Ju Choi & Byeong-Chan Oh & Moses Amoasi Acquah & Dong-Min Kim & Sung-Yul Kim, 2021. "Optimal Operation of a Hybrid Power System as an Island Microgrid in South-Korea," Sustainability, MDPI, vol. 13(9), pages 1-18, April.

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