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A two-layer energy management for islanded microgrid based on inverse reinforcement learning and distributed ADMM

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  • Huang, Lei
  • Sun, Wei
  • Li, Qiyue
  • Mu, Daoming
  • Li, Weitao

Abstract

The development of a scheduling strategy for an islanded microgrid (IMG) is critical for ensuring the system’s stability and economic efficiency. Traditional scheduling strategies for IMGs predominantly utilize centralized management by the microgrid central controller (MGCC), which introduces a vulnerability to a single point of failure. To address this limitation, this paper presents a two-layer energy management strategy for IMGs based on the improved alternating direction method of multipliers (ADMM) and inverse reinforcement learning (IRL). First, the framework of the proposed strategy, comprising a scheduling layer and a real-time dispatch layer, is outlined. Next, the problem formulation of the scheduling layer is analyzed, and the proposed IRL-based management strategy for the energy storage system (ESS) is presented. Then, a distributed optimization algorithm based on the improved ADMM is proposed for the management of controllable distributed generators (CDGs) in the real-time dispatch layer. Lastly, the case study demonstrates the efficacy of the proposed strategy in diminishing MGCC dependency. The comparative analysis indicates that the proposed strategy outperforms existing scheduling strategies in terms of cost-effectiveness when the forecast error exceeds 3%. Moreover, in contrast to existing scheduling strategies, the proposed strategy mitigates the risk associated with a single point of failure.

Suggested Citation

  • Huang, Lei & Sun, Wei & Li, Qiyue & Mu, Daoming & Li, Weitao, 2024. "A two-layer energy management for islanded microgrid based on inverse reinforcement learning and distributed ADMM," Energy, Elsevier, vol. 301(C).
    • Handle: RePEc:eee:energy:v:301:y:2024:i:c:s0360544224014452
    DOI: 10.1016/j.energy.2024.131672
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    References listed on IDEAS

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    1. Xin-gang, Zhao & Ze-qi, Zhang & Yi-min, Xie & Jin, Meng, 2020. "Economic-environmental dispatch of microgrid based on improved quantum particle swarm optimization," Energy, Elsevier, vol. 195(C).
    2. Li, Li & Dong, Mi & Song, Dongran & Yang, Jian & Wang, Qibing, 2022. "Distributed and real-time economic dispatch strategy for an islanded microgrid with fair participation of thermostatically controlled loads," Energy, Elsevier, vol. 261(PB).
    3. Lin, Zhiyi & Song, Chunyue & Zhao, Jun & Yin, Huan, 2022. "Improved approximate dynamic programming for real-time economic dispatch of integrated microgrids," Energy, Elsevier, vol. 255(C).
    4. Huang, Lei & Sun, Wei & Li, Qiyue & Li, Weitao, 2023. "Distributed real-time economic dispatch for islanded microgrids with dynamic power demand," Applied Energy, Elsevier, vol. 342(C).
    5. Tayab, Usman Bashir & Roslan, Mohd Azrik Bin & Hwai, Leong Jenn & Kashif, Muhammad, 2017. "A review of droop control techniques for microgrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 717-727.
    6. L. Xiao & S. Boyd, 2006. "Optimal Scaling of a Gradient Method for Distributed Resource Allocation," Journal of Optimization Theory and Applications, Springer, vol. 129(3), pages 469-488, June.
    Full references (including those not matched with items on IDEAS)

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