Application of GA based optimal integral gains in fuzzy based active power-frequency control of non-reheat and reheat thermal generating systems

Abstract

Optimal integral gains for nominal values of area input parameters and optimal transient responses of area frequency deviations as output with incremental increase of area load have been first computed by Genetic Algorithm (GA) technique for an interconnected, equal non-reheat and reheat type two generating areas. Optimal transient responses have been determined by using Sugeno fuzzy logic technique with GA based optimal gains and then with Matrix-Riccati based optimal gains [IEEE Trans. Power Syst. 14 (1999)] for various imprecise input area parameters. Results of comparative study show much improvement of transient responses in terms of settling times, undershoots, overshoots and df/dt in favor of GA based gains for non-reheat systems. Then, the same gains are applied for reheat systems, resulting in deterioration in performance, though less for GA based gains. So, for reheat systems again GA optimized gains have been computed and yield much improvement in performance. Performance for reheat systems is poorer than that of non-reheat systems owing to higher settling times and overshoots. Gains are also less than those for non-reheat systems. Then, the same analysis has been extended to three-area non-reheat and reheat systems. The same two-area based gains when applied to three-area systems yield poorer performance. Hence, to get better optimal performance GA based optimal gains have also been determined for three-area system, which are also much less compared with similar two-area systems and performance of three-area systems is also poorer than that of two-area systems.