Predictive control algorithms for congestion management in electric power distribution grids

•We propose a new control methodology for dealing with the congestion and balancing problems of the distribution grid.•The method is based on the Distributed Model Predictive Control architecture.•It optimizes the efficiency of the available demand response strategies.•The feasibility of the proposed method is tested on a benchmark smart grid under different scenarios. In this paper, model predictive control methodologies are developed to address two main issues which arise in electric power distribution systems, namely the congestion of the distribution lines and the balancing problem. Consumer energy demand is divided into an uncontrollable part, a controllable part that can be either stored in energy storage devices in order to be consumed at later times or shifted in time in the form of hourly consumption or a consumption that maintains a pattern. Demand – response strategies involve consumers actively in the balancing effort and are part of the MPC methodologies, which are formulated as Mixed Integer Quadratic Program optimization problems involving both continuous and binary variables. Finally, these new developments are tested on the IEEE European Low Voltage Test Feeder which highlights the performance of the proposed control schemes.