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Performance Analysis of Optimized Tuned Controllerfor Load Frequency Control

Mahesh Singh*, D.D. Neema**, R. N. Patel***

* Research Scholar, Department of Electrical Engineering, Swami Vivekananda Technical University, Bhilai (C.G.), India.

** Professor, Department of Electrical Engineering, CIT, Rajnandgaon (C.G.), India.

*** Professor, Department of Electrical and Electronics Engineering, Shri Shankaracharya Technical Campus, Bhilai, India.

Periodicity:December - February'2017
DOI : https://doi.org/10.26634/jcir.5.1.13546

Abstract

The nonlinear nature of the system behavior has several disturbances due to which the stability of the system gets affected. Controlled operation of power systems is very critical and the most important factor is to achieve stable power system. For this reason, there is a need of different adaptive control techniques. Therefore, for obtaining lesser modeling error in the system, different intelligent control techniques are used, which improves the power system operation. PID controllers are most commonly used as it is simple in operation. Therefore, several tuning techniques like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA) are being used for the optimum setting of PID controller parameters so as to improve the system stability. In this paper, the performance of different PID controller techniques is compared for four error minimization methods and is being applied to the load frequency control model that helps to identify optimum controller for an individual

Keywords

Transient Stability, Adaptive Control, PID Controllers, Load Frequency Control, Simulated Annealing, Genetic Algorithm, Particle Swarm Optimization, Integral Absolute Error, Integral Time Absolute Error, Integral Square Error, Integral Time Square Error

How to Cite this Article?

Singh, M., Neema, D. D., and Patel, R. N. (2017). Performance Analysis of Optimized Tuned Controller for Load Frequency Control. i-manager’s Journal on Circuits and Systems, 5(1), 36-43. https://doi.org/10.26634/jcir.5.1.13546

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