Opimal design for power system dynamic stabilizer by grey prediction PID control

被引:0
作者
Ding, CC [1 ]
Lee, KT [1 ]
Tsai, CM [1 ]
Huang, TL [1 ]
机构
[1] Tamkang Univ, Dept Elect Engn, Taipei, Taiwan
来源
IEEE ICIT' 02: 2002 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS I AND II, PROCEEDINGS | 2002年
关键词
power systems stability; grey prediction; genetic algorithms;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we proposed an effective method to design the, 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 system. Therefore, favor a control scheme that uses only some desired state variables, such as torque angle and speed. To deal with this problem, we use the optimal reduced models to reduce the power system model into two state variables system by each generator and use grey prediction PID control to find control signal of each generator. Moreover, we will apply genetic algorithms (GAs) to find the appropriate parameter values for the desired system. Finally, the advantages of the proposed method are illustrated by numerical simulation of the two machines-infinite-bus power systems.
引用
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页码:279 / 284
页数:6
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