Controller Tuning for Power System using Various Soft Computing Techniques

Abstract

newlineiv newlineABSTRACT newlineThe main aim of today s power generating system is to ensure that the supplied power to a specified area must be equal to its load demand with guarantee of reliability and stability. The frequency in the power system is controlled by the speed of governor mechanism via load frequency control (LFC). The terminal voltage of the governor is sensed by Automatic Voltage Regulator (AVR) which is utilized to adjust the excitations of the regulator so that constant terminal voltage may be obtained. From the past study it is clear that many conventional and intelligent controllers such as PI, PID controllers, optimal and adaptive controllers are utilized for LFC and AVR to control real power and reactive power of the power system. The load demand of power system changes significantly due to advancements in the development of power industries hence, these controllers having fixed gain are not able to provide better results under worst load conditions. The main aim of the controller is to provide output frequency and output voltage at the optimal value under every worst fluctuating load conditions. The PID controllers have the main parameters settling time, overshoot and oscillations. These parameters should be so designed such that the optimal results must be gained. Usually the control parameters of these controllers have been obtained by trial and error approach in which more time is consumed for execution of system to get the output results. In order to reduce these difficulty in tuning PID parameters, evolutionary computation techniques such as Fuzzy Logic, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) can be implemented. During the past several years intelligent fuzzy logic (FL) and artificial neural network (ANN) techniques has developed as a standout amongst the most dynamic and productive application in power system industries. Solar photovoltaic, wind energy, solar thermal power system, diesel engine generators (DEGs), fuel cells (FCs), battery energy storage system (BESS), flywheel (FW), ultra-capacitors (UCs) and aqua electrolyzes (AE) are emerging renewable energy techniques and can be developed as a viable option for generation of electric power in these days. In modern grids to maintain generation load balance due to the emerging of renewable energy sources more intelligent and flexible controllers are newlinev newlinerequired. In this work investigation in view of the dynamic execution of Load frequency Control (LFC) of three region hydro thermal power system interconnected with smart grid, (PV) photovoltaic power generation and (EV) Electric Vehicles by utilizing Artificial Intelligent and conventional controller is presented. In the proposed scheme, control methodology is developed using conventional PI, PID controller, intelligent Artificial Neural Network (ANN) and Fuzzy Logic controller (FLC), for two-area and three area hydro thermal reheat power system interconnected with smart grid. As the number of renewable energy sources are increasing day by day the power system become complex. The fluctuations in the system causes mismatch between power generation and load demand. The conventional controllers alone are not able to provide the desired output results. So to remove the gap between power generation and connected load demand an intelligent control technique based upon artificial neural network (ANN) for two area hydro thermal power system and for three area hydro-thermal power system with isolated photovoltaic power generation system using electrical vehicle integration is utilized. The performance of intelligent ANN controller is compared with conventional PID and intelligent fuzzy logic controller. It is proved that the proposed controller have less settling time and better dynamic response for the considered interconnected power system with proposed smart grid. As the electric vehicles are driven with the help of AC/DC supply so these vehicles have many important merits as compared to the other internal or external combustion engines. In these vehicles the motor torque generation is very fast and accurate, there is possibility to install motors on two