An Edge-Based Distributed Algorithm For Economic Dispatch In Power Systems

This paper proposes an edge-based distributed primal-dual algorithm for economic dispatch problem (EDP), in which a collection of networked generators cooperatively minimizes the sum of all local cost functions while satisfying some coupling constraints. Different from the existing results, this paper applies the techniques, such as the factorization of weighted Laplacian and the spectral decomposition, to prove the convergence of the proposed algorithm. It proves that the proposed distributed algorithm converges provided that the step-size is positive and lower than an exact upper bound. Strong convexity of each local cost function and Lipschitz continuity of its gradient are employed to ensure a linear convergence rate of the proposed algorithm. Finally, two numerical simulations are presented to show the performance of the proposed algorithm.