Data Driven Model Predictive Control Design to Enhance Tracking Accuracy and Power Quality of a Solar Based Microgrid under Uncertain Load

Abstract

Microgrid uses renewable energy sources to generate power and this is one of the most important reasons for drawing attention of researchers. Microgrid is a small scaled power generation unit which is a set of loads, distributed generation units, voltage source inverters, PCC, filters etc. Parameters and loads are unknown and uncertain which cause unmodeled dynamics of loads. Tracking performance of voltage degrades due to different uncertainties and unmodeled load dynamics of microgrid. This paper presents the design of a data driven model predictive controller to control the voltage of a single phase islanded microgrid. The way in which the controller is designed ensures robustness, guarantees performance and stability against unmodeled dynamics, unknown loads and all other uncertainties. MATLAB/SIMULINK is used to carry out the simulation of controller and the results are found for open and closed loop system. Under different load condition and uncertainties the performance of controller is studied. Results presented in this paper indicate stability, robustness, improved voltage quality and tracking performance under mentioned uncertain and unknown conditions.