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Optimal operation strategy for interconnected microgrids in market environment considering uncertainty

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  • Kong, Xiangyu
  • Liu, Dehong
  • Wang, Chengshan
  • Sun, Fangyuan
  • Li, Shupeng

Abstract

The interconnected microgrid system (IMS) is a promising solution for the problem of growing penetration of renewable-based microgrids into the power system. To optimally coordinate the operation of microgrids owned by different owners while considering uncertainties in market environment, a bi-level distributed optimized operation method for IMS with uncertainties is proposed in this paper. A hierarchical and distributed operational communication architecture of IMS is first established. A bi-level distributed optimization model was built for IMS, where at the upper level, the IMS operates purchase-sale mode or demand response mode with the distribution network operator and optimizes the trading power with microgrids to maximize revenue. At the lower level, the chance constraint programming is used to describe and deal with the uncertainty of renewable energy and loads and optimize the output and energy storage of distributed energy with the goal of minimum cost. The analytical target cascading and augmented Lagrange method are combined to decouple and reconstruct the bi-level model for distributed solution and establishing a fair price mechanism. The optimal solutions of the problem are obtained through parallel iteration, in which the price signal plays a coordinated role in the distributed iterative optimization process. Abundant case studies verify the advantages of the model and the performance of the proposed method.

Suggested Citation

  • Kong, Xiangyu & Liu, Dehong & Wang, Chengshan & Sun, Fangyuan & Li, Shupeng, 2020. "Optimal operation strategy for interconnected microgrids in market environment considering uncertainty," Applied Energy, Elsevier, vol. 275(C).
    • Handle: RePEc:eee:appene:v:275:y:2020:i:c:s0306261920308485
    DOI: 10.1016/j.apenergy.2020.115336
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    References listed on IDEAS

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    5. Chang, Weiguang & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Two-stage coordinated operation framework for virtual power plant with aggregated multi-stakeholder microgrids in a deregulated electricity market," Renewable Energy, Elsevier, vol. 199(C), pages 943-956.
    6. Wu, Chuantao & Zhou, Dezhi & Lin, Xiangning & Sui, Quan & Wei, Fanrong & Li, Zhengtian, 2022. "A novel energy cooperation framework for multi-island microgrids based on marine mobile energy storage systems," Energy, Elsevier, vol. 252(C).
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    11. Han, Dongho & Lee, Jay H., 2021. "Two-stage stochastic programming formulation for optimal design and operation of multi-microgrid system using data-based modeling of renewable energy sources," Applied Energy, Elsevier, vol. 291(C).
    12. Silva, Jéssica Alice A. & López, Juan Camilo & Arias, Nataly Bañol & Rider, Marcos J. & da Silva, Luiz C.P., 2021. "An optimal stochastic energy management system for resilient microgrids," Applied Energy, Elsevier, vol. 300(C).
    13. Wei, Chun & Shen, Zhuzheng & Xiao, Dongliang & Wang, Licheng & Bai, Xiaoqing & Chen, Haoyong, 2021. "An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining," Applied Energy, Elsevier, vol. 295(C).
    14. Ying-Yi Hong & Gerard Francesco DG. Apolinario, 2021. "Uncertainty in Unit Commitment in Power Systems: A Review of Models, Methods, and Applications," Energies, MDPI, vol. 14(20), pages 1-47, October.
    15. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
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