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Risk-limiting dispatching strategy considering demand response in multi-energy microgrids

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  • Nie, Yonghui
  • Qiu, Yu
  • Yang, Annan
  • Zhao, Yan

Abstract

Multi-energy microgrids deploy distributed power sources with flexible generation characteristics to meet the changing needs of users. Because they comprise renewable as well as traditional energy sources, they can play an important role in the transition to clean and efficient low-carbon power generation. However, both the complexity of coordinating different power sources and random fluctuations of renewable-energy generation capacity pose significant challenges. To solve these problems, a risk-limiting dispatching strategy for multi-energy microgrids is proposed that considers net load-demand response. First, a bi-directional demand-response mechanism is introduced, and a flexible load is used as a dispatchable resource to optimize the net load curve of the system. Second, entropy-based reliability modeling is conducted to address the multiple uncertainties in system operation. Third, a risk-limiting dispatching model of the multi-energy microgrid is established that considers three optimization objectives: economy, environmental protection, and reliability. Finally, the NSGA-III algorithm is used to obtain the set of optimal solutions for the model, and a compromise solution that meets the system operation requirements is selected based on the technique for order preference by similarity to an ideal solution (TOPSIS) with a criteria importance though intercriteria correlation (CRITIC) and analytic hierarchy process (AHP, CRITIC–AHP) hybrid assignment. The simulation results show that the proposed optimal scheduling strategy improves the operational reliability index while ensuring system economy and environmental protection. This study provides a new approach for controlling system risk and ensuring continuous energy-supply capability under uncertain conditions.

Suggested Citation

  • Nie, Yonghui & Qiu, Yu & Yang, Annan & Zhao, Yan, 2024. "Risk-limiting dispatching strategy considering demand response in multi-energy microgrids," Applied Energy, Elsevier, vol. 353(PA).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pa:s0306261923014526
    DOI: 10.1016/j.apenergy.2023.122088
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    Cited by:

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    2. Hua, Haochen & Du, Can & Chen, Xingying & Kong, Hui & Li, Kang & Liu, Zhao & Naidoo, Pathmanathan & Lv, Mian & Hu, Nan & Fu, Ming & Li, Bing, 2024. "Optimal dispatch of multiple interconnected-integrated energy systems considering multi-energy interaction and aggregated demand response for multiple stakeholders," Applied Energy, Elsevier, vol. 376(PA).
    3. Zhao, Wei & Shao, Zhen & Yang, Shanlin & Lu, Xinhui, 2025. "A novel conditional diffusion model for joint source-load scenario generation considering both diversity and controllability," Applied Energy, Elsevier, vol. 377(PC).
    4. Yin, Linfei & Cai, Zhenjian, 2024. "Multimodal multi-objective hierarchical distributed consensus method for multimodal multi-objective economic dispatch of hierarchical distributed power systems," Energy, Elsevier, vol. 295(C).

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