A hybrid stochastic fractal search and pattern search technique based cascade PI-PD controller for automatic generation control of multi-source power systems in presence of plug in electric vehicles

Abstract

A hybrid Stochastic Fractal Search plus Pattern Search (hSFS-PS) based cascade PI-PD controller is suggested in this paper for Automatic Generation Control (AGC) of thermal, hydro and gas power unit based power systems in presence of Plug in Electric Vehicles (PEV). Firstly, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral (I) controller is optimized by Stochastic Fractal Search (SFS) algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal control, differential evolution and teaching learning based optimization techniques is demonstrated by comparing simulation results for the identical power system. To improve the system performance further, Pattern Search (PS) is subsequently employed. The study is further extended for different controllers like PI, PID, and cascaded PI-PD controller and the superiority of cascade PI-PD controller over conventional controllers is demonstrated. Then, cascade PI-PD controller parameters of AGC searched using the proposed hSFS-PS algorithm in presence of plug in electric vehicles. The study is also extended to an interconnected power system. It is seen from the comparative analysis that hSFS-PS tuned PI-PD controller in single and multi-area with multi sources improves the system frequency stability in complicated situations. Lastly, a three area interconnected system with PEVs with dissimilar cascade PI-PD controller in each area is considered and proposed hSFS-PS algorithm is used to tune the controller parameters in presence of nonlinearities like rate constraint of units, dead zone of governor and communication delay.