可控制动电阻的模糊神经网络控制  

FUZZY NEURAL NETWORK CONTROL OF THYRISTOR CONTROLLED BRAKING RESISTANCE(TCBR)

作　　者：付蓉[1] 韩敬东[1] 鞠平[1] 倪辉[1] 

机构地区：[1]河海大学电气学院,江苏省南京市210098

出　　处：《电网技术》2001年第2期13-16,共4页Power System Technology

基　　金：国家自然科学基金资助项目(59677014)

摘　　要：可控制动电阻 (TCBR)的电阻值可以随时连续调节 ,这为改善系统稳定性提供了有效的手段。文章首先定性分析了 TCBR的阻尼原理 ,证明在适当条件下可以提供正阻尼 ;然后应用一种改进的模糊神经网络自适应控制系统 ,设计了TCBR的控制器。仿真计算结果表明 ,TCBR的模糊神经网络控制对静态稳定性和暂态稳定性均具有良好效果。Thyristor controlled breaking resistor (TCBR) is a new FACTS element, in which the resistor is controlled by thyristor and can be adjusted continuously at any time, so it provides an effective measure to improve system stability. In this paper firstly the damping principle of TCBR is analyzed, and it is proved that under appropriate condition the positive damping could be obtained. Then, applying adaptive control system based on improved fuzzy neural network, a TCBR controller is designed. The results of simulation calculation show that the fuzzy neural network control possesses good effect for both steady stability and transient stability.

关 键 词：可控制动电阻 神经网络 模糊控制 

分 类 号：TM712[电气工程—电力系统及自动化]