Distributed Multi-Period DCOPF via an Auxiliary Principle Problem Algorithm

Distributed algorithms provide attractive features for solving Optimal Power Flow (OPF) problems in interconnected power systems compared to traditional centralized algorithms. Distributed algorithms help to maintain the control autonomy and data privacy of subsystems, which is particularly relevant in competitive markets and practical control system implementations. This paper analyzes a distributed optimization algorithm known as the 'Auxiliary Principle Problem' to solve multiperiod distributed DCOPF problems with distributed energy resources including energy storage systems. The proposed approach enables multiple interconnected systems with their own sub-objectives to share their resources and to participate in an electricity market without implicitly sharing information about their local generators or internal network parameters. The paper also shows how the proposed approach can enable future microgrids to coordinate their operation, reduce the total operational cost, and avoid internal constraint violations caused by unscheduled flows (USF) while maintaining the subsystems' autonomy. We use an 11-bus test system consisting of two interconnected subsystems to evaluate the proposed approach and analyze the impact of USF.