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In this paper, a novel efficient robust model predictive control (RMPC) strategy is proposed for the intraday energy management of IES, which has less conservativeness and more economical performance. Two dimensions of uncertainty factors are introduced to flexibly model the renewable energy and loads and the robust degree can be adjusted according to the operation requirement. A real-time feedback module is introduced to update the allocation plan of the dispatchable units online, which significantly improves the feasibility of the scheduling plan. Comprehensive simulation studies with the comparison of the state-of-the-art methods demonstrate the effectiveness of the proposed RMPC strategy.

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Dynamic Energy Management for Integrated Energy System in Industrial Parks Based on Robust Model Predictive Control

  • 会议论文

  • 发表日期：

    2025年

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  • Jiawen Xu,
  • Zhuoli Zhao,
  • Yu Liang,
  • Chang Liu,
  • Lei Yu,
  • Xuntao Shi,
  • Loi Lei Lai

摘要

In this paper, a novel efficient robust model predictive control (RMPC) strategy is proposed for the intraday energy management of IES, which has less conservativeness and more economical performance. Two dimensions of uncertainty factors are introduced to flexibly model the renewable energy and loads and the robust degree can be adjusted according to the operation requirement. A real-time feedback module is introduced to update the allocation plan of the dispatchable units online, which significantly improves the feasibility of the scheduling plan. Comprehensive simulation studies with the comparison of the state-of-the-art methods demonstrate the effectiveness of the proposed RMPC strategy.