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The coordinated alternating current optimal power flow (ACOPF) for coupledtransmission-distribution grids has become crucial to handle problems relatedto high penetration of renewable energy sources (RESs). However, obtaining allsystem details and solving ACOPF centrally is not feasible because of privacyconcerns. Intermittent RESs and uncontrollable loads can swiftly change theoperating condition of the power grid. Existing decentralized optimizationmethods can seldom track the optimal solutions of time-varying ACOPFs. Here, wepropose an online decentralized optimization method to track the time-varyingACOPF of coupled transmission-distribution grids. First, the time-varying ACOPFproblem is converted to a dynamic system based on Karush-Kuhn-Tucker conditionsfrom the control perspective. Second, a prediction term denoted by the partialderivative with respect to time is developed to improve the tracking accuracyof the dynamic system. Third, a decentralized implementation for solving thedynamic system is designed based on only a few information exchanges withrespect to boundary variables. Moreover, the proposed algorithm can be used todirectly address nonlinear power flow equations without relying on convexrelaxations or linearization techniques. Numerical test results reveal theeffectiveness and fast-tracking performance of the proposed algorithm.

Online decentralized tracking for nonlinear time-varying optimal power flow of coupled transmission-distribution grids