Model Predictive Control for Power Quality Enhancement in Grid-Tied Renewable Energy Inverters

Abstract

The project aims at applying Model Predictive Control (MPC) to increase the power quality of grid-tied inverters connected to photovoltaic (PV) and wind systems. The presence of increased renewable energy on the power grid has led to an increased possibility of occurrence of harmonic distortion, voltage variations and a decline in quick response that may compromise the grid and violate power quality norms such as IEEE 519. Conventional controllers like proportional--integral (PI) and hysteresis control cannot always produce the correct result in a response to system dynamics and various properties of systems. These problems are eliminated in the framework which predicts what will take place in the system and switch the inverter appropriately to minimize a given cost function. With this solution, harmonics rejection and efficient current monitoring as well as rapid adaptation to grid issues and changed demand are realized. Simulation study In MATLAB / Simulink, the comparison of the proposed MPC controller against conventional control methods was achieved through simulation with different irradiance variations and loads being switched on / off. The results state that MPC-based inverter control introduces THD of less than 3%, ensures that the voltage remains in a range of +/- 2 percent of the nominal value and enables quicker transient responses, renovating renewable energy systems more dependable and compliant. Besides, MPC enables safety and control properties that makes it flexible to suit the future needs in smart grids. This method brings a practical solution that highly benefits a power grid to operate normally, provide high power quality and operate effectively with increased renewable energy, promoting the usage of intelligent inverters within the power supply system.