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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.
- University of North Texas United States
- Aalborg University Library (AUB) Denmark
- Pacific Northwest National Laboratory United States
- Aalborg University Library (AUB) Aalborg Universitet Research Portal Denmark
- Pacific Northwest National Laboratory United States
Control and Optimization, Consensus and gradient algorithm, Multi-agent systems, Multi-step optimization, Smart grid, 22/4 OA procedure, Energy storage (ES), Distributed coordination, SDG 7 - Affordable and Clean Energy
Control and Optimization, Consensus and gradient algorithm, Multi-agent systems, Multi-step optimization, Smart grid, 22/4 OA procedure, Energy storage (ES), Distributed coordination, SDG 7 - Affordable and Clean Energy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).63 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
