Publication

Abstract : Frequency control becomes a crucial issue as the integration of renewable energy sources and load fluctuation grow increasingly common in power networks. For two area power systems, this research study suggests a Genetic Algorithm (GA)-based frequency management strategy, taking into account the difficulties given by load variability and intermittent supply from renewable sources. The goal is to keep system frequency within reasonable bounds while guaranteeing effective use of the resources at hand. The suggested method makes use of GA to enhance the frequency regulation system's control parameters. The GA algorithm adapts control settings dynamically to changing system circumstances by taking into account load changes and intermittent generation. The method aims to reduce frequency variations, increase the use of renewable energy sources, and improve system stability in general. Realistic load profiles and intermittent generation patterns are incorporated into simulation experiments on a two-area power system model. Proportional-Integral (PI) and fuzzy logic controllers, as well as more conventional control techniques, are used to compare the performance of the GA-based frequency regulation strategy. The findings show that the GA-based strategy successfully controls system frequency, reduces frequency deviations brought on by demand changes and intermittent production, and maximizes the usage of renewable energy sources. The GA algorithm also offers resilient and adaptive control, allowing the system to adapt successfully to changing circumstances. The research's findings aid in the creation of sophisticated frequency control methods for power networks with high renewable energy penetration and changeable load profiles. The issues of integrating intermittent generating sources and preserving system stability in the face of load changes may be overcome using the GA-based method.