Online Distributed Algorithm for Optimal Power Flow problem with Regret Analysis
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Publication:6419901
arXiv2212.03921MaRDI QIDQ6419901
Author name not available (Why is that?)
Publication date: 7 December 2022
Abstract: In this article, we investigate the distributed DC-Optimal Power Flow (DC-OPF) problem against a backdrop of online convex optimization with coupled constraints. While the classical OPF problem refers to a time-invariant optimization environment across the power distribution network, the online variant involves time-varying objectives and equality constraints, with the cost functions gradually being disclosed to the generating agents in the network. The agents (generators and loads) in the network are only privy to their own local objectives and constraints. To this end, we address the problem by proposing a distributed online algorithm based on the modified primal-dual approach, which deals with the online equality-constrained issue. It has been theoretically demonstrated that the proposed algorithm exhibits a sublinearly bounded extit{static} regret and constraint violation with a suitable choice of descending stepsizes. Finally, we corroborate the results by illustrating them with numerical examples.
Has companion code repository: https://github.com/darknorth0/online_distributed_OPF
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