Model predictive control based frequency regulation of microgrid with integration of distributed energy resources

Abstract

Power generation sector has become more prevalent in the use of renewable energy sources resulting in more complex and non-linear network. Microgrids are becoming the best alternative solution in remote areas where the distribution network is infeasible. However, the intermittent nature of distributed renewable energy resources can result in a generation and demand mismatch instigating frequency variation which is a crucial concern. Thus, modern power system requires increasing intelligence and flexibility to cope up with the generation-load mismatch. Efficient control techniques are of vital importance in maintaining the frequency near the nominal value, and the selection of the controller is crucial in maintaining the reliable, effective, and steady functioning of the power system. The present study demonstrates frequency control in islanded microgrid with disruptions in load demand using the model predictive control by efficiently managing the energy storage with integration of large-scale renewable energy sources. The effectiveness and superiority of the proposed model predictive controller (MPC) is presented by comparing its performance with proportional integral controller and proportional integral tuned with adaptive neuro fuzzy inference system (ANFIS) through simulations in MATLAB environment.