Hybridizing rule-based power system stabilizers with geneticalgorithms

摘要

A hybrid genetic rule-based power system stabilizer (GRBPSS) isnpresented in this paper. The proposed approach uses genetic algorithmsn(GA) to search for optimal settings of rule-based power systemnstabilizer (RBPSS) parameters. Incorporation of GA in RBPSSs design willnadd an intelligent dimension to these stabilizers and significantlynreduce the time consumed in the design process. It is shown in thisnpaper that the performance of RBPSS can be improved significantly bynincorporating a genetic-based learning mechanism. The performance of thenproposed GRBPSS under different disturbances and loading conditions isninvestigated for a single machine infinite bus system and twonmultimachine power systems. The results show the superiority of thenproposed GRBPSS as compared to both conventional lead-lag PSS (CPSS) andnclassical RBPSS. The capability of the proposed GRBPSS to damp out thenlocal as well as the interarea modes of oscillations is alsondemonstrated