Innovative Control of Two-Stage Grid-Connected Solar Inverter Based on Genetic Algorithm Optimization

Abstract

Grid-connected photovoltaic systems are now being employed in the power system more and more as a result of their decreasing cost and increased competitiveness in comparison to other power plants. However, because the generated energy is low-voltage DC, it is crucial to change the voltage so that it is compatible with the distribution system (single-phase AC or 3-phase AC). All grid levels should have intelligence injected, and that intelligence should have a long-lasting effect. In order to help utility engineers to better assess the possible effects of these new power sources on the system, this article provides new research tools and approaches. Therefore, a unique PV solar system control approach is suggested by this research. The strategy is an optimized grid-connected solar system control approach. In this regard, it is crucial to design a controller that is good at reducing Power Stress inside the PV System. In this study, the power delivered by the PV system has been controlled and stabilized by using the Proportional Integral Derivative (PID) controller in combination with the Genetic Algorithm (GA) heuristic approach. Then the GA technique has been utilized to identify the ideal settings, based on the performance of Integrated Time Absolute Error (ITAE). The simulation results show that the PV system can successfully monitor the required performance.