Optimization of Automatic Generation Control Performance for Power System of Two-Area based on Genetic Algorithm-Particle Swarm Optimization

The purposes of automatic generation control (AGC) in a power system are to control the interchange of tie-line schedule in various power system regions, maintain the frequency within the required range and distribute the load among different generators. Thus, it is important to ensure that the performance of AGC is at its optimum level. One of the methods to optimum the performance of AGC is by implementing PID or proportional-integral-derivative controllers. In this project, the performance of AGC for power system of two-area is optimized using a properly tuned PID controllers via combination of particle swarm optimization (PSO) and genetic algorithm (GA) algorithms or GA-PSO. The proposed method was compared with AGC with PID controllers but without optimized by any algorithm and optimized using GA and PSO. According to the results, it was observed that combination of GA-PSO is able to optimize the AGC with PID controllers better than without optimization and using PSO and GA alone.