In this paper, we consider the problem of optimally coordinating the response of a group of distributed energy resources (DERs) to meet total electric power demand while minimizing the total generation cost and respecting the DER capacity limits. This problem can be cast as a convex optimization problem, where the global objective is to minimize a sum of convex functions corresponding to the costs of generating power from the DERs while satisfying linear inequality constraints corresponding to the DER capacity limits and a linear equality constraint corresponding to the total power generated by the DERs being equal to the total power demand. We develop distributed algorithms to solve the DER coordination problem over time-varying communication networks with either (i) bidirectional or (ii) unidirectional communication links. The algorithms proposed for directed communication graphs have the geometric convergence rate when communication out-degrees are unknown to agents. The algorithms can be seen as the distributed versions of a centralized primal-dual algorithm. We showcase the algorithms using the standard IEEE 39-bus test system, and compare their performance against that of existing ones.
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