摘要
首先建立了单机—无穷大系统的数学模型,并进行了可逆性分析。将神经网络具有的对非线性系统的逼近能力以及对系统参数变化的适应能力与逆系统方法的解耦线性化特点相结合,提出了基于神经网络逆系统的电力系统稳定器的设计方法,并进行了仿真研究。动态仿真分析表明,该电力系统稳定器能够有效地增加系统的阻尼,提高系统的稳定性。
Firstly, mathematical model of a generator system in a Single Machine Infinite Bus (SMIB) System was developed, and the reversibility of the system was analyzed. Based on artificial neural networks, a novel method to design power system stabilizer for a SMIB was proposed. This method combines approximation ability to nonlinear system and adaptability to parameters variation of artifi- cial neural networks and decoupling characteristic of inverse system. Emulational study has been carried out. By the dynamic...
出处
《微计算机信息》
北大核心
2008年第1期200-202,共3页
Control & Automation
关键词
单机无穷大系统
数学模型
逆系统
神经网络
电力系统稳定器
single machine infinite bus system
mathematical model
reverse system
neural networks
power system stabilizer
