Scaling Distributed Optimal Renewable Energy Coordination in Unbalanced Distribution Systems

The increased installation of renewable grid-edge assets into an already complex power distribution system has driven extensive development of distributed optimal power flow (OPF) methods to coordinate such assets. However, existing distributed optimization algorithms applied to unbalanced systems require many communication-rounds among the distributed agents and may pose convergence challenges. Besides, the communication network parameters also significantly impact the algorithm's performance. In this paper, we propose a scalable, equivalent network approximation-based, distributed OPF method that employs a communication infrastructure using cyber-physical co-simulation platform to coordinate grid-edge renewable assets for three-phase unbalanced distribution systems. Additionally, the robustness of the proposed approach is validated under stressed communication scenarios. The results are thoroughly compared with the state-of-the-art algorithms and equivalent centralized optimal power flow (C-OPF) problems for medium IEEE-123 Bus Test system and large-scale PNNL R3-12.47-2 feeder distribution test systems.