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Stochastic Unit Commitment Problem, Incorporating Wind Power and an Energy Storage System

Author

Listed:
  • Khalid Alqunun

    (Department of Electrical Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia)

  • Tawfik Guesmi

    (Department of Electrical Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia
    National Engineering School of Sfax, University of Sfax, Sfax 3038, Tunisia)

  • Abdullah F. Albaker

    (Department of Electrical Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia)

  • Mansoor T. Alturki

    (Department of Electrical Engineering, University of Ha’il, Ha’il 2240, Saudi Arabia)

Abstract

This paper presents a modified formulation for the wind-battery-thermal unit commitment problem that combines battery energy storage systems with thermal units to compensate for the power dispatch gap caused by the intermittency of wind power generation. The uncertainty of wind power is described by a chance constraint to escape the probabilistic infeasibility generated by classical approximations of wind power. Furthermore, a mixed-integer linear programming algorithm was applied to solve the unit commitment problem. The uncertainty of wind power was classified as a sub-problem and separately computed from the master problem of the mixed-integer linear programming. The master problem tracked and minimized the overall operation cost of the entire model. To ensure a feasible and efficient solution, the formulation of the wind-battery-thermal unit commitment problem was designed to gather all system operating constraints. The solution to the optimization problem was procured on a personal computer using a general algebraic modeling system. To assess the performance of the proposed model, a simulation study based on the ten-unit power system test was applied. The effects of battery energy storage and wind power were deeply explored and investigated throughout various case studies.

Suggested Citation

  • Khalid Alqunun & Tawfik Guesmi & Abdullah F. Albaker & Mansoor T. Alturki, 2020. "Stochastic Unit Commitment Problem, Incorporating Wind Power and an Energy Storage System," Sustainability, MDPI, vol. 12(23), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:23:p:10100-:d:455630
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    References listed on IDEAS

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    Cited by:

    1. Sukita Kaewpasuk & Boonyarit Intiyot & Chawalit Jeenanunta, 2025. "A Fuzzy Unit Commitment Model for Enhancing Stability and Sustainability in Renewable Energy-Integrated Power Systems," Sustainability, MDPI, vol. 17(15), pages 1-21, July.
    2. Young-Been Cho & Yun-Sung Cho & Jae-Gul Lee & Seung-Chan Oh, 2021. "Design and Implementation of Probabilistic Transient Stability Approach to Assess the High Penetration of Renewable Energy in Korea," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    3. Mahmoud Rihan & Aml Sayed & Adel Bedair Abdel-Rahman & Mohamed Ebeed & Thamer A H Alghamdi & Hossam S Salama, 2024. "An artificial gorilla troops optimizer for stochastic unit commitment problem solution incorporating solar, wind, and load uncertainties," PLOS ONE, Public Library of Science, vol. 19(7), pages 1-28, July.
    4. Cheng-Ta Tsai & Yu-Shan Cheng & Kuen-Huei Lin & Chun-Lung Chen, 2021. "Effects of a Battery Energy Storage System on the Operating Schedule of a Renewable Energy-Based Time-of-Use Rate Industrial User under the Demand Bidding Mechanism of Taipower," Sustainability, MDPI, vol. 13(6), pages 1-15, March.
    5. Ebrie, Awol Seid & Kim, Young Jin, 2024. "Reinforcement learning-based optimization for power scheduling in a renewable energy connected grid," Renewable Energy, Elsevier, vol. 230(C).

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