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Integrated Energy Microgrid Economic Dispatch Optimization Model Based on Information-Gap Decision Theory

Author

Listed:
  • Xiaowei Fan

    (State Grid Chongqing Electric Power Company, Chongqing 400014, China)

  • Yongtao Chen

    (Electric Power Scientific Research Institute of State Grid Chongqing Electric Power Company, Chongqing 401121, China)

  • Ruimiao Wang

    (Electric Power Scientific Research Institute of State Grid Chongqing Electric Power Company, Chongqing 401121, China)

  • Jiaxin Luo

    (State Grid Wulong Power Supply Company, Chongqing 408506, China)

  • Jingang Wang

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 400044, China)

  • Decheng Cao

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 400044, China)

Abstract

To address the problems of “difficult to consume” renewable energy and the randomness of power output, we propose the CHP unit joint-operation model with power to gas (P2G) and carbon capture system (CCS) technologies and analyze the operation cost, carbon emission, and “electric-heat coupling” characteristics of this model. A dispatch optimization model is constructed based on the information-gap decision theory under the strategy to further consider the interval uncertainty of renewable energy unit output and load forecast. The optimized-dispatching model effectively solves the fate of renewable unit output and electric-thermal load and provides dispatching strategies for decision-makers to balance risk and capital management.

Suggested Citation

  • Xiaowei Fan & Yongtao Chen & Ruimiao Wang & Jiaxin Luo & Jingang Wang & Decheng Cao, 2023. "Integrated Energy Microgrid Economic Dispatch Optimization Model Based on Information-Gap Decision Theory," Energies, MDPI, vol. 16(8), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3314-:d:1118473
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    References listed on IDEAS

    as
    1. Pang, Qinghua & Dong, Xianwei & Zhang, Lina & Chiu, Yung-ho, 2023. "Drivers and key pathways of the household energy consumption in the Yangtze river economic belt," Energy, Elsevier, vol. 262(PA).
    2. Amigues, Jean-Pierre & Kama, Alain Ayong Le & Moreaux, Michel, 2015. "Equilibrium transitions from non-renewable energy to renewable energy under capacity constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 89-112.
    3. Wang, Xiaojing & Han, Li & Wang, Chong & Yu, Hongbo & Yu, Xiaojiao, 2023. "A time-scale adaptive dispatching strategy considering the matching of time characteristics and dispatching periods of the integrated energy system," Energy, Elsevier, vol. 267(C).
    4. Yang, Ting & Zhao, Liyuan & Li, Wei & Zomaya, Albert Y., 2021. "Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning," Energy, Elsevier, vol. 235(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    integrated energy; information-gap decision theory; P2G;
    All these keywords.

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