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Robust Optimal Scheduling of Integrated Energy Systems Considering the Uncertainty of Power Supply and Load in the Power Market

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  • Lang Zhao

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
    State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Yuan Zeng

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Zhidong Wang

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Yizheng Li

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Dong Peng

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

  • Yao Wang

    (Economic and Technical Research Institute, State Grid Shanxi Electric Power Company, Taiyuan 030002, China)

  • Xueying Wang

    (State Grid Economic and Technological Research Institute Co., Ltd., Beijing 102209, China)

Abstract

The integrated energy system is a complex energy system that involves multi-stakeholder and multi-energy coordinated operations. The key to improving its scale and sustainable development is to construct a better-integrated energy system dispatching method which is suitable for the power market. However, the randomness of the supply side and load side of the integrated energy system brings further challenges to system planning and scheduling. Therefore, the optimal scheduling method of an integrated energy system considering the uncertainty of supply and demand in the market environment is studied in this paper. Firstly, the uncertainty models of the supply side and load side of the integrated energy system are established. Then, the optimal scheduling model based on robust chance constraint is established. The reserve capacity constraint is set as a chance constraint with a certain confidence level to maximize the system profit in the power market. Finally, simulations show that the proposed method not only guarantees the robustness of the system but also improves the economy of the system. The method provides ideas for exploring the development mechanism and strategy of integrated energy systems in the electricity market environment.

Suggested Citation

  • Lang Zhao & Yuan Zeng & Zhidong Wang & Yizheng Li & Dong Peng & Yao Wang & Xueying Wang, 2023. "Robust Optimal Scheduling of Integrated Energy Systems Considering the Uncertainty of Power Supply and Load in the Power Market," Energies, MDPI, vol. 16(14), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5292-:d:1191373
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    References listed on IDEAS

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    1. Fatma Zehra Doğru & Olcay Arslan, 2021. "Finite mixtures of skew Laplace normal distributions with random skewness," Computational Statistics, Springer, vol. 36(1), pages 423-447, March.
    2. Iver Bakken Sperstad & Magnus Korpås, 2019. "Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties," Energies, MDPI, vol. 12(7), pages 1-24, March.
    3. Tengfei Ma & Junyong Wu & Liangliang Hao & Huaguang Yan & Dezhi Li, 2018. "A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach," Energies, MDPI, vol. 11(10), pages 1-19, October.
    4. Jiang, Tao & Zhang, Rufeng & Li, Xue & Chen, Houhe & Li, Guoqing, 2021. "Integrated energy system security region: Concepts, methods, and implementations," Applied Energy, Elsevier, vol. 283(C).
    5. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    6. Min Li & Chao Zhang, 2020. "Two-Stage Stochastic Variational Inequality Arising from Stochastic Programming," Journal of Optimization Theory and Applications, Springer, vol. 186(1), pages 324-343, July.
    7. Fulya Gokalp Yavuz & Olcay Arslan, 2018. "Linear mixed model with Laplace distribution (LLMM)," Statistical Papers, Springer, vol. 59(1), pages 271-289, March.
    8. Sinha, Shyamalendu & Hart, Jeffrey D., 2019. "Estimating the mean and variance of a high-dimensional normal distribution using a mixture prior," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 201-221.
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