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The optimal power flow (OPF) problem, which plays a central role in operatingelectrical networks is considered. The problem is nonconvex and is in fact NPhard. Therefore, designing efficient algorithms of practical relevance iscrucial, though their global optimality is not guaranteed. Existingsemi-definite programming relaxation based approaches are restricted to OPFproblems where zero duality holds. In this paper, an efficient novel method toaddress the general nonconvex OPF problem is investigated. The proposed methodis based on alternating direction method of multipliers combined withsequential convex approximations. The global OPF problem is decomposed intosmaller problems associated to each bus of the network, the solutions of whichare coordinated via a light communication protocol. Therefore, the proposedmethod is highly scalable. The convergence properties of the proposed algorithmare mathematically substantiated. Finally, the proposed algorithm is evaluatedon a number of test examples, where the convergence properties of the proposedalgorithm are numerically substantiated and the performance is compared with aglobal optimal method.

A Distributed Approach for the Optimal Power Flow Problem Based on ADMM and Sequential Convex Approximations