Distributed Optimal Coordination for Distributed Energy Resources in Power Systems

Driven by smart grid technologies, distributed energy resources (DERs) have been rapidly developing in recent years for improving reliability and efficiency of distribution systems. Emerging DERs require effective and efficient coordination in order to reap their potential benefits. In this paper, we consider an optimal DER coordination problem over multiple time periods subject to constraints at both system and device levels. Fully distributed algorithms are proposed to dynamically and automatically coordinate distributed generators with multiple/single storages. With the proposed algorithms, the coordination agent at each DER maintains only a set of variables and updates them through information exchange with a few neighbors. We show that the proposed algorithms with properly chosen parameters solve the DER coordination problem as long as the underlying communication network is connected. The simulation results are used to illustrate and validate the proposed method. Note to Practitioners—This paper was motivated by the problem of coordinating distributed energy resources (DERs) in order to increase the reliability and efficiency of distribution systems. Existing approaches are centralized, where a single control center gathers information from and provides control signals to the entire system. This centralized control framework may be subjected to performance limitations, such as high communication requirement and cost, substantial computational burden, limited flexibility, and disrespect of privacy. To overcome these limitations and accommodate various resources in the future smart grid, in this paper, we develop an alternative distributed control strategy, where each DER communicates only with its neighbors, without a need for a central coordinator. In this paper, only distributed generators and energy storage devices are considered. In future research, we will extend the proposed algorithms to include other types of flexible resources, such as thermostatically controlled loads, plug-in electric vehicles, and deferrable loads.