Bio-inspired fuzzy logic based tuning of power system stabilizer
In this paper, bacteria foraging optimization (BFO)  a bio-inspired technique, is utilized to tune the parameters of both single-input and dual-input power system stabilizers (PSSs). Conventional PSS (CPSS) and the three dual-input IEEE PSSs (PSS2B, PSS3B, and PSS4B) are optimally tuned to obtain the optimal transient performances. A comparative performance study of these four variants of PSSs is also made. It is revealed that the transient performance of dual-input PSS is better than single-input PSS. It is, further, explored that among dual-input PSSs, PSS3B offers superior transient performance. A comparison between the results of the BFO and that of genetic algorithm (GA) is conducted in this study. The comparison reveals that BFO is more effective than GA in finding the optimal transient performance. For on-line, off-nominal operating conditions Sugeno fuzzy logic (SFL) based approach is adopted. On real time measurements of system operating conditions, SFL adaptively and very fast yields on-line, off-nominal optimal stabilizer parameters.
bacteria foraging optimization dual-input power system stabilizer genetic algorithm sugeno fuzzy logic conventional power system stabilizer