Abstract—The phenomenon of Stability of Modern Power Systems has received a great deal of attention in recent years. With the increasing complexity of the Modern Power Systems, the system stability is affected by Low frequency oscillations produced in the system. This paper provides a systematic approach to design a damping controller to damp the oscillations based on Bio inspired Genetic Algorithm (GA).The design problem is formulated as an Multiobjective Optimization criterion comprising of Eigen value based and Time domain based objective functions to compute the optimal controller parameters. The main objective here is to shift the closed loop eigen values to better positions in s plane and also to minimize the integral squared error involving rotor speed and power angle deviations so that the system stability will be enhanced to a greater extent. To validate the effectiveness and robustness of the proposed controller, Non linear simulations has been implemented under various system operating conditions and also introduction of disturbances in the form of outage of Transmission line in the system considered. The proposed controller design is also compared with the conventional Lead lag controller design to show the importance of the proposed Bio inspired controller design.
Index Terms-netic Algorithm, Multiobjective function, Power System Stability, Robust Control.
R. Shivakumar is with Department of Electrical and Electronics Engineering, Sona College of Technology, Salem-636005, Tamilnadu, India (email : email@example.com).
R. Lakshmipathi is with Department of Electrical and Electronics Engineering, St. Peters Engineering College, Chennai, India(email :firstname.lastname@example.org).
Y. Suresh is with Department of Information Technology, Sona College of Technology, Salem-636005,Tamilnadu, India (email :email@example.com).
Cite: R. Shivakumar, R. Lakshmipathi and Y. Suresh, "Implementation of Bio Inspired Genetic Optimizer in enhancing Power System Stability," International Journal of Engineering and Technology vol. 2, no. 3, pp. 263-268, 2010.