Dynamic Power Distribution System Management with a Locally Connected Communication Network
Coordinated optimization and control of distribution-level assets can enable a reliable and optimal integration of massive amount of distributed energy resources (DERs) and facilitate distribution system management (DSM). Two challenges exist for this network-wide coordination problem: i) the possibly disconnected communication network; and ii) the system dynamics from the variable DERs/loads and measurement error. This talk will develop the modeling and algorithm design for DSM considering these two factors. First, a game-theoretic characterization is proposed to address a locally connected communication network over DERs, along with the existence/uniqueness analysis of the Nash equilibrium. Second, a projected-gradient based asynchronous DSM algorithm is advocated for distributed equilibrium learning. Its convergence speed and tracking error are analyzed under dynamic system setting. This is joint work with Kaiqing Zhang and Tamer Basar at UIUC, Wei Shi at ASU, and Emiliano Dall’Anese at NREL.
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