Agnihotri Piyush; International Journal of Advance Research, Ideas and Innovations in Technology. © 2017, IJARIIT All Rights Reserved Page | 966 ISSN: 2454-132X Impact factor: 4.295 (Volume3, Issue1) Available online at: www.ijariit.com Stabilization Of Power System Using Artificial Intelligence Based System Piyush Agnihotri Department of Electrical & Electronics Engineering Pranveer Singh Institute of Technology, Kanpur, INDIA piyushagnihotri034@gmail.com Jitendra Kumar Dwivedi Department of Electrical Engineering Harcourt Butler Technical University Kanpur, INDIA jkdwivedi.hbti@gmail.com Vishnu Mohan Mishra Department of Electrical Engineering GB Pant Engineering College, Pauri-Garhwal vmm66@rediffmail.com Abstract— This paper reviews limitations of traditional control system and modern control system controllers, which are overcome to some extent using artificial intelligent techniques, such as ANN, Fuzzy Logic, Expert System, Particle Swarm Optimization, Genetic Algorithm, etc. The review shows that efforts are made towards Power System Stabilizer based on Artificial Intelligent Techniques, which will give positive impact on the system stabilities and improve system performances. Keywords—ANN; PSO; Fuzzy Logic; Genetic Algorithm. I. INTRODUCTION Power system engineering forms a vast and major portion of electrical engineering studies. It is mainly concerned with the production of electrical power and its transmission from the sending end to the receiving end as per consumer requirements, incurring minimum amount of losses. The power at the consumer end is often subjected to changes due to the variation of load or due to disturbances induced within the length of transmission line. For this reason the term power system stability is of utmost importance in this field, and is used to define the ability of the of the system to bring back its operation to steady state condition within minimum possible time after having undergone some sort of transience or disturbance in the line. Ever since the 20th century, till the recent times all major power generating stations over the globe has mainly relied on AC distribution system as the most effective and economical option for the transmission of electrical power. The Automatic Voltage Regulator (AVR) and exciter are the main components of the generator excitation system. The terminal generator voltage sensed and compared with the reference voltage to control the exciter output. Subsequent to any disturbance the damper and the field winding attempt to damp rotor swing. The damping process repels by the negative damping torques introduced by AVR. As a result, the power system may expose undesirable oscillations or lose synchronism. For this concern, the Power System Stabilizer (PSS) become technologically advanced and expanded to serve for an effective functioning. The main function of the PSS in the excitation system is introducing an additional signal to provide a damping component that is in the phase with the rotor speed deviation. Therefore, the System Stability will be enhanced by adding PSS device. Stabilizers that developed according to classical and modern control theories are based on liberalized machine model. Power system is a nonlinear, complex system and is subjected to different kinds of disturbances that yield unresolved issues and uncertain consequences in different power system problems. With such limitations, it is difficult to stabilize power system efficiency by these kinds of PSSs. Therefore, other types of modern control techniques like adaptive controller and H ∞ control system were used to achieve better operating performance as distinguished from conventional stabilizers. Artificial Intelligence (AI) techniques proved to be effective tools to resolve many power system problems and those they could be more effective when properly joined together with conventional mathematical approaches were proposed based on these AI techniques. In this work, a serious attempt is made to present a comprehensive analysis of artificial intelligent techniques for designing PSS, which are proposed by researchers recently. The performance of a variety of controllers is demonstrated and compared with other types of controllers.