Distributed Multi-Period Optimal Power Flow for Demand Response in Microgrids

Abstract

The scalability and privacy preserving nature of distributed optimisation techniques makes them ideal for coordinating many independently acting agents in a microgrid setting. However, their practical applicability remains an open question in this context, since AC power flows are inherently non-convex and households make discrete decisions about how to schedule their loads. In this paper, we show that one such method, the alternating direction method of multipliers (ADMM), can be adapted to remain practical in this challenging microgrid setting. We formulate and solve a multi-period optimal power flow (OPF) problem featuring independent households with shiftable loads, and study the results obtained with a range of power flow models and approaches to managing discrete decisions. Our experiments on a suburb-sized microgrid show that the AC power flows and a simple two-stage approach to handling discrete decisions do not appear to cause convergence issues, and provide near optimal results in a time that is practical for receding horizon control. This work brings distributed control for microgrids several steps closer to reality.