Distributed Time-Varying Optimal Resource Management for Microgrids via Fixed-Time Multiagent Approach

Tingting Zhou, Salah Laghrouche and Youcef Ait-Amirat ()
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Tingting Zhou: FEMTO-ST Institute, Centre National de la Recherche Scientifique (CNRS), UTBM, Université Marie et Louis Pasteur, F-90000 Belfort, France
Salah Laghrouche: FEMTO-ST Institute, Centre National de la Recherche Scientifique (CNRS), UTBM, Université Marie et Louis Pasteur, F-90000 Belfort, France
Youcef Ait-Amirat: FEMTO-ST Institute, Centre National de la Recherche Scientifique (CNRS), UTBM, Université Marie et Louis Pasteur, F-90000 Belfort, France

Energies, 2025, vol. 18, issue 10, 1-24

Abstract: This paper investigates the distributed time-varying (TV) resource management problem (RMP) for microgrids (MGs) within a multi-agent system (MAS) framework. A novel fixed-time (FXT) distributed optimization algorithm is proposed, capable of operating over switching communication graphs and handling both local inequality and global equality constraints. By incorporating a time-decaying penalty function, the algorithm achieves an FXT consensus on marginal costs and ensures asymptotic convergence to the optimal TV solution of the original RMP. Unlike the prior methods with centralized coordination, the proposed algorithm is fully distributed, scalable, and privacy-preserving, making it suitable for real-time deployment in dynamic MG environments. Rigorous theoretical analysis establishes FXT convergence under both identical and nonidentical Hessian conditions. Simulations on the IEEE 14-bus system validate the algorithm’s superior performance in convergence speed, plug-and-play adaptability, and robustness to switching topologies.

Keywords: distributed time-varying optimization; multi-agent systems; optimal resource management; fixed-time; switching graphs (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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