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A Cloud–Edge Collaborative Multi-Timescale Scheduling Strategy for Peak Regulation and Renewable Energy Integration in Distributed Multi-Energy Systems

Author

Listed:
  • Zhilong Yin

    (Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710061, China)

  • Zhiyuan Zhou

    (Power Dispatch Control Center, State Grid Shaanxi Electric Power Co., Ltd., Xi’an 710048, China)

  • Feng Yu

    (School of Electrical Engineering, Nantong University, Nantong 226019, China)

  • Pan Gao

    (Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710061, China)

  • Shuo Ni

    (Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710061, China)

  • Haohao Li

    (Xi’an Dynamic Inspection and Testing Co., Ltd., Xi’an 710061, China)

Abstract

Incorporating renewable energy sources into the grid poses challenges due to their volatility and uncertainty in optimizing dispatch strategies. In response, this article proposes a cloud–edge collaborative scheduling strategy for distributed multi-energy systems, operating across various time scales. The strategy integrates day-ahead dispatch, intra-day optimization, and real-time adjustments to minimize operational costs, reduce the wastage of renewable energy, and enhance overall system reliability. Furthermore, the cloud–edge collaborative framework helps mitigate scalability challenges. Crucially, the strategy considers the multi-timescale characteristics of two types of energy storage systems (ESSs) and three types of demand response (DR), aimed at optimizing resource allocation efficiently. Comparative simulation results evaluate the strategy, providing insights into the significant impacts of different ESS and DR types on system performance. By offering a comprehensive approach, this strategy aims to address operational complexities. It aims to contribute to the seamless integration of renewable energy into distributed systems, potentially enhancing sustainability and resilience in energy management.

Suggested Citation

  • Zhilong Yin & Zhiyuan Zhou & Feng Yu & Pan Gao & Shuo Ni & Haohao Li, 2024. "A Cloud–Edge Collaborative Multi-Timescale Scheduling Strategy for Peak Regulation and Renewable Energy Integration in Distributed Multi-Energy Systems," Energies, MDPI, vol. 17(15), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3764-:d:1446317
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    References listed on IDEAS

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    1. Pan, Zhaoguang & Guo, Qinglai & Sun, Hongbin, 2016. "Interactions of district electricity and heating systems considering time-scale characteristics based on quasi-steady multi-energy flow," Applied Energy, Elsevier, vol. 167(C), pages 230-243.
    2. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "Hybrid time-scale energy optimal scheduling strategy for integrated energy system with bilateral interaction with supply and demand," Applied Energy, Elsevier, vol. 285(C).
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