Multi-machine Adaptive Power System Stabilizer via Radial Basis Function Network

Dulyatat Nualhong and Songsak Chusanapiputt

Department of Electrical Engineering, Faculty of Engineering

Mahanakorn University of Technology, Bangkok, 10530, Thailand

Manuscript received December 28, 2001,

Revised May 10, 2002





This paper presents the effectiveness of adaptive power system stabilizers (APSS) via the radial basis function network (RBFN). To have good damping characteristics over a wide range of operating conditions. The proposed RBFN uses orthogonal least square (OLS) learning that was programmed over a full working range of the generating units with a variety of load conditions. The results compare for a small-signal stability with application to the three-machine system shows the superiority of the proposed RBFN APSS, which can provide a better performance than conventional power system stabilizers (CPSS).



Keywords: Power system stabilizer, Radial basis function network, Power system stability

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