Improving the Frequency Response of Microgrid Using GA-Optimized PI Controllers

The addition of sources of clean electricity, such as wind, photovoltaic (PV), even hydroelectric power, is posing issues for frequency regulation in electrical grids. The intermittent nature of environmental factors like wind and sunlight introduces uncertainty in renewable energy generation, intensifying frequency management challenges as wind and PV penetration increases. To address these issues, advanced control strategies are essential for managing power system operations under diverse conditions. This study proposes using a Genetic Algorithm (GA) for optimizing the Proportional-Integral (PI) controllers, enhancing frequency stability, particularly under fault conditions. The approach seeks to reduce the Integral of Time Absolute Error (ITAE) to identify the ideal parameters for the controller used for the PI. Numerical simulations are used to validate the proposed method and show that the optimization approach improves the performance of the Load Frequency Control (LFC).