An initialization-free distributed prescribed-time optimization algorithm based on multiagent systems for solving economic dispatch problem

doi:10.1016/j.neucom.2025.131890

An initialization-free distributed prescribed-time optimization algorithm based on multiagent systems for solving economic dispatch problem

2025-10-22

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DOI：10.1016/j.neucom.2025.131890

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In this paper, the economic dispatch problem (EDP) is investigated, aiming at scheduling a cluster of generators to fulfill the supply–demand balance and capability limitations at the minimized cost, where the generators in a system communicate over undirected and connected communication networks. For solving the EDP, a distributed initialization-free prescribed-time optimization approach is designed. On account of Lyapunov stability analysis and convex optimization theory, the algorithm proposed herein is proved scrupulously to converge to the optimal solutions of EDP within a prescribed time. Distinct from both the distributed finite-time optimization approaches (where the settling time heavily depends on incipient conditions) and the distributed fixed-time optimization approaches (where the settling-time cannot be arbitrarily pre-specified), the designed method herein has prescribed-time convergence and optimality. Moreover, an upper bound of the settling time function of the dynamic system is independent of controller gains and incipient conditions, implying that the convergence time of the presented algorithm can be preset under any allowable range physically. Lastly, three examples are put forward to validate the efficiency of theoretical results.

An initialization-free distributed prescribed-time optimization algorithm based on multiagent systems for solving economic dispatch problem

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