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<p>A chance-constrained energy dispatch model based on the distributed stochastic model predictive control (DSMPC) approach for an islanded multi-microgrid system is proposed. An ambiguity set considering the inherent uncertainties of renewable energy sources (RESs) is constructed without requiring the full distribution knowledge of the uncertainties. The power balance chance constraint is reformulated within the framework of the distributionally robust optimization (DRO) approach. With the exchange of information and energy flow, each microgrid can achieve its local supply-demand balance. Furthermore, the closed-loop stability and recursive feasibility of the proposed algorithm are proved. The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.</p>

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Distributed stochastic model predictive control for energy dispatch with distributionally robust optimization

  • 期刊论文

  • 发表日期：

    2025年1月30日

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  • Mengting Lin,
  • Bin Li,
  • C. Cecati

摘要

A chance-constrained energy dispatch model based on the distributed stochastic model predictive control (DSMPC) approach for an islanded multi-microgrid system is proposed. An ambiguity set considering the inherent uncertainties of renewable energy sources (RESs) is constructed without requiring the full distribution knowledge of the uncertainties. The power balance chance constraint is reformulated within the framework of the distributionally robust optimization (DRO) approach. With the exchange of information and energy flow, each microgrid can achieve its local supply-demand balance. Furthermore, the closed-loop stability and recursive feasibility of the proposed algorithm are proved. The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.