Hybrid Optimal Control of a Single Input and a Dual Input Power System Stabilizer

V. Mukherjee and S.P. Ghoshal (India)




: This paper presents an overall comparative performance study of two hybrid techniques of optimizations of two different types of power system stabilizer (PSS) parameters in a SMIB system. The hybrid techniques are Genetic Algorithm-Sugeno Fuzzy Logic control (GA-SFL) and Hybrid Particle Swarm Optimization with Constriction Factor Approach-Sugeno Fuzzy Logic Control (HPSOCFA-SFL). The power system stabilizers are Single Input Conventional Power System Stabilizer (CPSS) and IEEE dual input type PSS4B. Rigorous computer simulation study shows HPSOCFA-SFL based IEEE dual input type IEEEPSS4B to be more robust optimal power system stabilizer in damping all electromechanical modes of generator's angular speed oscillations for all off-line and on-line system operating conditions such as step changes of mechanical torque inputs and reference voltage inputs and during / after clearing of system faults. Moreover, HPSOCFA is also better and faster off-line optimizing tool as compared with GA. Sugeno Fuzzy Logic is used as a very fast, on-line manipulator of off-line optimal PSS parameters with on-line varying system operating conditions.

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