Plug in hybrid vehicle-wind-diesel autonomous hybrid power system: frequency control using FA and CSA optimized controller

Large integration of renewable energy in hybrid power system in isolated mode of operation make frequency control a challenging task. This paper investigates the performance of Cuckoo Search Algorithm (CSA) and Firefly Algorithm (FA) based frequency control strategy of such a hybrid power system, which is a unique work. The generating units of the system are plug in hybrid vehicle (PHEV), wind turbine generators, a diesel engine generator (DEG) and battery energy storage system (BESS). The proportional plus integral (PI)/proportional integral derivative (PID) controllers are employed with PHEV, DEG and BESS to adjust the total active power generation in accordance to the load demand. Addition of PHEV reduces the reliance on the DEG or BESS as a result of variability and uncertainty of wind power. Different disturbance conditions such as step perturbations, random variations of load as well as wind output power, have been considered in the case studies under Matlab simulation to assess the performance of CSA and FA based control strategy. Analysis indicates that CSA based PID controller provides better response compare to GA, PSO and FA based PI/PID controller and CSA based PI controller. Sensitivity analysis has been carried out to check the robustness of FA and CSA optimized PI/PID controller gains.