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Stochastic Distributed Control for Arbitrarily Connected Microgrid Clusters

Author

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  • Maryam Khanbaghi

    (Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA 95053, USA)

  • Aleksandar Zecevic

    (Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA 95053, USA)

Abstract

Due to the success of single microgrids, the coming years are likely to see a transformation of the current electric power system to a multiple microgrid network. Despite its obvious promise, however, this paradigm still faces many challenges, particularly when it comes to the control and coordination of energy exchanges between subsystems. In view of that, in this paper we propose an optimal stochastic control strategy in which microgrids are modeled as stochastic hybrid dynamic systems. The optimal control is based on the jump linear theory and is used as a means to maximize energy storage and the utilization of renewable energy sources in islanded microgrid clusters. Once the gain matrices are obtained, the concept of ε -suboptimality is applied to determine appropriate levels of power exchange between microgrids for any given interconnection pattern. It is shown that this approach can be efficiently applied to large-scale systems and guarantees their connective stability. Simulation results for a three microgrid cluster are provided as proof of concept.

Suggested Citation

  • Maryam Khanbaghi & Aleksandar Zecevic, 2022. "Stochastic Distributed Control for Arbitrarily Connected Microgrid Clusters," Energies, MDPI, vol. 15(14), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5163-:d:864117
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    References listed on IDEAS

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    1. Zhilin Lyu & Xiao Yang & Yiyi Zhang & Junhui Zhao, 2020. "Bi-Level Optimal Strategy of Islanded Multi-Microgrid Systems Based on Optimal Power Flow and Consensus Algorithm," Energies, MDPI, vol. 13(7), pages 1-19, March.
    2. Maryam Khanbaghi & Aleksandar Zecevic, 2020. "Jump Linear Quadratic Control for Microgrids with Commercial Loads," Energies, MDPI, vol. 13(19), pages 1-21, September.
    3. Bullich-Massagué, Eduard & Díaz-González, Francisco & Aragüés-Peñalba, Mònica & Girbau-Llistuella, Francesc & Olivella-Rosell, Pol & Sumper, Andreas, 2018. "Microgrid clustering architectures," Applied Energy, Elsevier, vol. 212(C), pages 340-361.
    4. Kou, Peng & Liang, Deliang & Gao, Lin, 2017. "Distributed EMPC of multiple microgrids for coordinated stochastic energy management," Applied Energy, Elsevier, vol. 185(P1), pages 939-952.
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    Cited by:

    1. Maciej Sołtysik & Karolina Mucha-Kuś & Jacek Kamiński, 2022. "The New Model of Energy Cluster Management and Functioning," Energies, MDPI, vol. 15(18), pages 1-18, September.

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