The main objective of the work is to design a Load frequency controller to minimize frequency deviations using two Novel Soft computing techniques. Two types of Power system configurations are considered for analysis such as single area thermal power system integrated with Hybrid Distributed generation resources comprising of Wind turbine generator, Solar PV system, Diesel engine generator, Fuel cell with aqua electrolyzer and Battery energy storage system and two area interconnected power system with Distributed generation in area-1. The inclusion of Wind and Solar energy with high variability in its output power is a challenging task for effective controller design. The control scheme chosen in this paper is PID controller whose parameters are tuned by two different novel Soft computing techniques such as Salp Swarm Algorithm (SSA), Grasshopper Optimization Algorithm (GOA). The robustness of the PID controllers is demonstrated on the two types of power systems under different loading conditions. The results illustrated that the SSA technique based PID controller gives better controlling action compared to other PID controllers.
Hybrid power system, Distributed generation, PID controller, Frequency control, Soft computing techniques, MATLAB/SIMULINK, Salp Swarm Algorithm (SSA), Grasshopper Optimization Algorithm (GOA), and Particle Swarm Optimization (PSO).