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Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties

Author

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  • Mohammed Atta Abdulgalil

    (Electrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

  • Muhammad Khalid

    (Electrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
    K.A.CARE Energy Research & Innovation Center, Dhahran 31261, Saudi Arabia)

  • Fahad Alismail

    (Electrical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
    K.A.CARE Energy Research & Innovation Center, Dhahran 31261, Saudi Arabia)

Abstract

In this paper, based on stochastic optimization methods, a technique for optimal sizing of battery energy storage systems (BESSs) under wind uncertainties is provided. Due to considerably greater penetration of renewable energy sources, BESSs are becoming vital elements in microgrids. Integrating renewable energy sources in a power system together with a BESS enhances the efficiency of the power system by enhancing its accessibility and decreasing its operating and maintenance costs. Furthermore, the microgrid-connected BESS should be optimally sized to provide the required energy and minimize total investment and operation expenses. A constrained optimization problem is solved using an optimization technique to optimize a storage system. This problem of optimization may be deterministic or probabilistic. In case of optimizing the size of a BESS connected to a system containing renewable energy sources, solving a probabilistic optimization problem is more effective because it is not possible to accurately determine the forecast of their output power. In this paper, using the stochastic programming technique to discover the optimum size of a BESS to connect to a grid-connected microgrid comprising wind power generation, a probabilistic optimization problem is solved. A comparison is then produced to demonstrate that solving the problem using stochastic programming provides better outcomes and to demonstrate that the reliability of the microgrid improves after it is connected to a storage system. The simulation findings demonstrate the efficacy of the optimum sizing methodology proposed.

Suggested Citation

  • Mohammed Atta Abdulgalil & Muhammad Khalid & Fahad Alismail, 2019. "Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties," Energies, MDPI, vol. 12(12), pages 1-29, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2412-:d:242341
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    2. Fahad Alismail & Mohamed A. Abdulgalil & Muhammad Khalid, 2021. "Optimal Coordinated Planning of Energy Storage and Tie-Lines to Boost Flexibility with High Wind Power Integration," Sustainability, MDPI, vol. 13(5), pages 1-17, February.
    3. Feras Alasali & Mohammad Salameh & Ali Semrin & Khaled Nusair & Naser El-Naily & William Holderbaum, 2022. "Optimal Controllers and Configurations of 100% PV and Energy Storage Systems for a Microgrid: The Case Study of a Small Town in Jordan," Sustainability, MDPI, vol. 14(13), pages 1-20, July.
    4. Gulam Smdani & Muhammad Remanul Islam & Ahmad Naim Ahmad Yahaya & Sairul Izwan Bin Safie, 2023. "Performance Evaluation Of Advanced Energy Storage Systems: A Review," Energy & Environment, , vol. 34(4), pages 1094-1141, June.
    5. Han, Seungyun & Kobla Tagayi, Roland & Kim, Jaewon & Kim, Jonghoon, 2022. "Adaptive deterministic approach for optimized sizing of high-energy battery system applied in electric-powered application," Applied Energy, Elsevier, vol. 309(C).
    6. Thirunavukkarasu, M. & Sawle, Yashwant & Lala, Himadri, 2023. "A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    7. Navid Shirzadi & Fuzhan Nasiri & Ursula Eicker, 2020. "Optimal Configuration and Sizing of an Integrated Renewable Energy System for Isolated and Grid-Connected Microgrids: The Case of an Urban University Campus," Energies, MDPI, vol. 13(14), pages 1-18, July.
    8. Nahid-Al Masood & Md. Nahid Haque Shazon & Hasin Mussayab Ahmed & Shohana Rahman Deeba, 2020. "Mitigation of Over-Frequency through Optimal Allocation of BESS in a Low-Inertia Power System," Energies, MDPI, vol. 13(17), pages 1-23, September.
    9. Abdul Rauf & Mahmoud Kassas & Muhammad Khalid, 2022. "Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty," Sustainability, MDPI, vol. 14(17), pages 1-27, September.

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