A scalable distributed online algorithm for optimal power flow in distribution system

Abstract

In this paper, a scalable distributed online algorithm is proposed for solving optimal power flow (OPF) in real time. The operation of distribution systems can be continuously driven towards given OPF targets only depending on local and some aggregated information of each distribution area. Particularly, the proposed algorithm is applicable to the distribution system where each area operates in arbitrary topologies. The algorithm uses the primal-dual gradient method to update DER set-points recurrently based on the sensitivities of the OPF targets; moreover, we decompose the sensitivities into several separate items and give the method to calculate these separate items in a distributed way. The decomposition and distributed calculation methods are all deduced under the general power flow model that completely specifies the physics of electrical networks with arbitrary topologies. The effectiveness of the algorithm is verified using a modified 502-node distribution system. Compared with the online algorithms requiring to process some operation details in a centralized way, the proposed algorithm can achieve almost the same convergence properties with reducing the calculation time sharply.