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Optimal Sizing and Location of Photovoltaic Generation and Energy Storage Systems in an Unbalanced Distribution System

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  • Ming-Yuan Chiang

    (Department of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, Taiwan)

  • Shyh-Chour Huang

    (Department of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, Taiwan)

  • Te-Ching Hsiao

    (Department of Mechanical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, Taiwan)

  • Tung-Sheng Zhan

    (Department of Electrical Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 807618, Taiwan)

  • Ju-Chen Hou

    (Department of Electrical Engineering, Kao-Yuan University, Kaohsiung City 82151, Taiwan)

Abstract

There has been an increasing number of renewable energy sources introduced into the distribution system to decrease the dependence on single power sources and relieve their effects related to global warming caused by power consumption. When greatly increasing renewable energy in the power system, the renewable energy connected to the power grid must be coupled with corresponding energy-storage technologies. This mechanism not only effectively improves the power floating problem but also more efficiently re-dispatches the power output. The purpose of this paper is to deal with the optimal sizing and location issue of the photovoltaic generation system and the battery energy storage system, which are proposed in order to improve the power loss, bus voltage profile, and voltage unbalance for the actual unbalanced loading distribution system of a large-scale chemical factory. The power loss, construction cost of the solar power and the energy storage systems, voltage variation ratio and voltage unbalance ratio will be treated as part of the objective function of the optimal problem. These variables are subject to various operating constraints and the voltage variation limit of the system when the photovoltaic generation and battery energy storage systems are operated. Furthermore, a refined genetic algorithm, which possesses an auto-selective crossover and mutation scheme, is proposed and applied in this paper in order to solve the optimization problem. Moreover, the simulation results are expected to demonstrate the superiority of the proposed algorithm.

Suggested Citation

  • Ming-Yuan Chiang & Shyh-Chour Huang & Te-Ching Hsiao & Tung-Sheng Zhan & Ju-Chen Hou, 2022. "Optimal Sizing and Location of Photovoltaic Generation and Energy Storage Systems in an Unbalanced Distribution System," Energies, MDPI, vol. 15(18), pages 1-22, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6682-:d:913337
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    References listed on IDEAS

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    1. Temitayo O. Olowu & Aditya Sundararajan & Masood Moghaddami & Arif I. Sarwat, 2018. "Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey," Energies, MDPI, vol. 11(7), pages 1-32, July.
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    Cited by:

    1. Hajra Khan & Imran Fareed Nizami & Saeed Mian Qaisar & Asad Waqar & Moez Krichen & Abdulaziz Turki Almaktoom, 2022. "Analyzing Optimal Battery Sizing in Microgrids Based on the Feature Selection and Machine Learning Approaches," Energies, MDPI, vol. 15(21), pages 1-22, October.
    2. Soheil Younesi & Bahman Ahmadi & Oguzhan Ceylan & Aydogan Ozdemir, 2022. "Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems," Energies, MDPI, vol. 15(24), pages 1-18, December.

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