ptimized automatic generation control using single and multiobjective GA and DE techniques
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 9
Abstract
In this paper both single and multi objective genetic algorithm and differential evolution optimization techniques are applied to tune PID parameters for the application of automatic generation control of two area six units non reheat thermal power plant. The controllers are optimized by considering 0.1 step load disturbance for area 1 only and computed with sum of absolute value of ith area control error at time t as objective functions. While employing multi objective GA and DE optimization techniques, best compromise solution of the corresponding PID parameters are obtained based on fuzzy membership function assignment technique. Performance and comparison analysis of GA-PID and DE-PID is done using both single and multi objective optimization techniques and according to the result, the optimized value result obtained by DE is getting better than GA in achieving lesser settling time, undershoot and overshoot in AGC application. Further more, for more realistic and confidential the simulation results obtained from the suggested controllers are compared with that of the simulation obtained from without applying the controller.
Authors and Affiliations
Solomon Feleke, K. Vaisakh
Keywords
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