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Optimal Allocation of Photovoltaic Systems and Energy Storage Systems based on Vulnerability Analysis

Author

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  • Ryusuke Konishi

    (Graduate School of Science and Technology, Keio University, Yokohama 223-0061, Japan
    Japan Science and Technology Agency (JST), CREST, Kawaguchi 332-0012, Japan)

  • Masaki Takahashi

    (Faculty of Science and Technology, Keio University, Yokohama 223-0061, Japan
    Japan Science and Technology Agency (JST), CREST, Kawaguchi 332-0012, Japan)

Abstract

There is a growing need to connect renewable energy systems (REs), such as photovoltaic systems (PVs), to the power grid for solving environmental problems such as global warming. However, an electricity grid with RE is vulnerable to problems of power shortage and surplus owing to the uncertainty of RE outputs and grid failures. Energy storage systems (ESSs) can be used to solve supply reliability problems, but their installation should be minimized considering their high costs. This study proposes a method to optimize the allocations of PVs and ESSs based on vulnerability analysis, and utilizes our proposed concept of “slow” and “fast” ESSs, which can reflect the influences of both uncertainties: PV outputs and grid failures. Accordingly, this paper demonstrates an optimal allocation of PVs and ESSs that minimizes the amount of ESSs while satisfying the PV installation target and the constraints on supply reliability indices for power shortage and power surplus in the event of a grid failure.

Suggested Citation

  • Ryusuke Konishi & Masaki Takahashi, 2017. "Optimal Allocation of Photovoltaic Systems and Energy Storage Systems based on Vulnerability Analysis," Energies, MDPI, vol. 10(10), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1477-:d:113027
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    References listed on IDEAS

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    1. Zio, E. & Golea, L.R., 2012. "Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 67-74.
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    Cited by:

    1. Zezhong Li & Xiangang Peng & Yilin Xu & Fucheng Zhong & Sheng Ouyang & Kaiguo Xuan, 2023. "A Stackelberg Game-Based Model of Distribution Network-Distributed Energy Storage Systems Considering Demand Response," Mathematics, MDPI, vol. 12(1), pages 1-21, December.
    2. Pimnapat Bhumkittipich & Hideaki Ohgaki, 2018. "Development Strategy for Sustainable Solar Home System in the Akha Upland Community of Thailand," Energies, MDPI, vol. 11(6), pages 1-14, June.
    3. Ahmed Alzahrani & Hussain Alharthi & Muhammad Khalid, 2019. "Minimization of Power Losses through Optimal Battery Placement in a Distributed Network with High Penetration of Photovoltaics," Energies, MDPI, vol. 13(1), pages 1-16, December.
    4. Ikeda, Shunnosuke & Nishimura, Naoki & Sukegawa, Noriyoshi & Takano, Yuichi, 2023. "Prescriptive price optimization using optimal regression trees," Operations Research Perspectives, Elsevier, vol. 11(C).
    5. Ryusuke Konishi & Akiko Takeda & Masaki Takahashi, 2018. "Optimal Sizing of Energy Storage Systems for the Energy Procurement Problem in Multi-Period Markets under Uncertainties," Energies, MDPI, vol. 11(1), pages 1-19, January.
    6. Tsianikas, Stamatis & Zhou, Jian & Birnie, Dunbar P. & Coit, David W., 2019. "Economic trends and comparisons for optimizing grid-outage resilient photovoltaic and battery systems," Applied Energy, Elsevier, vol. 256(C).
    7. Gonocruz, Ruth Anne Tanlioco & Yoshida, Yoshikuni & Ozawa, Akito & Aguirre, Rodolfo A. & Maguindayao, Edward Joseph H., 2023. "Impacts of agrivoltaics in rural electrification and decarbonization in the Philippines," Applied Energy, Elsevier, vol. 350(C).
    8. Zhou, Jian & Tsianikas, Stamatis & Birnie, Dunbar P. & Coit, David W., 2019. "Economic and resilience benefit analysis of incorporating battery storage to photovoltaic array generation," Renewable Energy, Elsevier, vol. 135(C), pages 652-662.

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