Abstract
In this paper, we present a distributed economic dispatch strategy for a multi-area power system. We treat each generator and load in the grid as an “agent”. Due to the large-scale number of the agents, the agents in the same area can be sorted as one group and each group has a leader to communicate with its neighboring areas. The agents in the same group can communicate synchronously while the leader agent of each group exchange information in a random sequential way. By decomposing the centralized optimization into optimizations at local agents, a scheme is proposed for each agent to iteratively estimate a solution of the optimization problem in a distributed manner. It is shown that the estimated solutions of all the agents reach consensus of the optimal solution asymptomatically. Different from most existing distributed methods, private confidential information such as gradient or incremental cost of each generator is not required for information exchange, which makes more sense in real applications. Besides, the proposed method not only handles quadratic but also non-quadratic convex cost functions with arbitrary initial values. A case study implemented on IEEE 30-bus power system are discussed and tested to validate the proposed method.
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