Utilizing Electric Vehicles and Renewable Energy Sources for Load Frequency Control in Deregulated Power System Using Emotional Controller

Abstract

Modern day power system comprises of distributed power generation sources (DGs), distributed energy storage devices and loads. Control of these systems is more tedious than ordinary power systems since energy in these systems is provided by renewable energy sources which have intermittent and varying nature. These fluctuations in the generated power may cause some problems in the function of conventional controllers. As a result, the present-day power systems require increased intelligence and flexibility in control to ensure generation–load balance. In this paper, emotional controller (Brain Emotional Learning-Based Intelligent Controller, BELBIC) is used for load frequency control of two area hybrid power system in deregulated environment. The power system is integrated with DG sources like solar and biomass. Electric vehicles are used to handle intermittency of solar power. To make it more realistic, effect of nonlinearity constraints and time delay in communication channel is also considered. The proposed controller based on the emotional learning process of the human brain provides a suitable control action against system imperfections and occurrence of uncertainties. The special feature of this controller that makes it effective is its flexibility; its five gain parameters that give freedom to choose the desired response. To evaluate the performance of the proposed controller, the results are compared with the conventional proportional integral derivative (PID) and fractional order PID controller. Simulation results show the effectiveness of the emotional controller. Also, the parameters of the BELBIC are tuned by using Sugeno fuzzy inference system. Lyapunov stability analysis is used to prove the convergence of the designed control signals and to ensure the stability of the system.