Role of communication on the convergence rate of fully distributed DC optimal power flow

In a grid with highly distributed resources, an effective distributed algorithm for solving Optimal Power Flow (OPF) will result in efficient resource allocation across the system. This paper investigates the impact of communication on the performance of a fully distributed DC OPF algorithm, which solves the first order optimality conditions through an iterative process. In this distributed algorithm, at each iteration, every bus exchanges information with its physically connected neighboring buses and updates the local variables by evaluating a simple function. This paper suggests that sharing additional information between buses without physical connections across the system can speed up the convergence of the algorithm. A key aspect is the constrained selection of these additional communication links and the effective integration of this information in the update of the local variables which is the focus of this paper. A proof of concept is given using the IEEE-118 bus test system as a test case.