Coordinated scheduling of integrated transmission and distribution systems using an improved Lipschitz dynamic programming approach

Abstract

In this study, we propose an improved Lipschitz dynamic programming-based decentralized algorithm for the coordinated scheduling of integrated transmission and distribution (T&D) systems, considering unit commitments in a transmission system and the AC power flow and discrete control devices in distribution systems. In this algorithm, reverse norm cuts are introduced iteratively to approximate the value functions of subproblems of distribution systems, which are formulated as mixed-integer linear programming models. Based on the characteristics of subproblems of distribution systems, two strategies for introducing the reverse norm cuts in the subproblem of the transmission system are developed to improve the convergence. Furthermore, to further accelerate the proposed decentralized algorithm, a curve-fitting approach is designed to obtain the pre-defined approximate lower bounds of the value functions of distribution systems at each scheduling time period, which are formulated as a linear constraint set with integer variables. Finally, case studies are conducted on a constructed integrated T&D system and a practical integrated T&D system to verify the accuracy and effectiveness of the proposed algorithm.