Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices

Abstract This paper uses a Grasshopper Optimization Algorithm (GOA) optimized PDF plus (1 + PI) controller for Automatic generation control (AGC) of power system with Flexible AC Transmission (FACTS) devices. Three differently rated reheat turbine operated thermal units appropriate rate constraint (GRC) are considered along different FACTS A new multistage design structure is introduced in the empowered AGC while gains tuned by GOA. The superiority proposed algorithm over Genetic (GA) and Particle Swarm (PSO) algorithms demonstrated. dynamic responses GOA compared PIDF, PID PI controllers on same system. It demonstrated that provides optimum terms settling time peak deviations to other controllers. In addition, GOA-tuned Interline Power Flow Controller (IPFC) exhibits optimal results sturdiness projected validated using sensitivity analysis numerous load patterns wide variation parameterization. To further validate real-time feasibility method, experiments OPAL-RT OP5700 RCP/HIL FPGA based simulations carried out.