Variable Structure Power System Stabilizer Via Genetic Algorithm

• Main Authors: Pei-Ju Chen, 陳珮如
• Other Authors: Tsong-Liang Huang
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/72304258294597802585

碩士 === 國立臺北教育大學 === 資訊科學系碩士班 === 101 === This thesis proposes a new approach for using genetic algorithm to design variable structure power system stabilizers (PSS). The design of a PSS can be formulated as an optimal linear regulator control problem. However, implementing this technique requires the design of estimators. This increases the implementation and reduces the reliability of control systems. These reasons, therefore, favor a control scheme that uses only some desires state variables, such as torque angle and speed. To deal with this problem, this thesis uses the optimal reduced models to reduce the power system model into two state variables system by each generator. This thesis uses the genetic algorithm to find the switching surface vector and switching control signals, propose an approach “fuzzifier fitness function” to improve the search effect of genetic algorithms, and use variable structure control to find control signal of the generator. Finally, the advantages of the proposed method are illustrated by numerical simulation of the one and two machines-infinite-bus power systems.