继电器2001，Vol.29Issue(2)：13-15,19,4.
基于GPS同步量测量的模糊神经网络用于暂态稳定预测研究
Power systems transient stability prediction by using fuzzy neural network based on GPS synchronized measurements
苏建设 1廖培金 2周佃民2
作者信息
- 1. 上海交通大学电力系,
- 2. 西安交通大学电力系,
- 折叠
摘要
Abstract
This paper presents a transient stability prediction method inwhich a fuzzy neural network can, on the basis of GPS synchronized generator angles, predict whether the power systems is stable or not after large disturbances. This approach has fully exploited the advantages of fuzzy logic and neural network, i.e., integrating the expert's experience, learning from the sample set, extracting automatically the fuzzy rules and optimizing the membership functions, etc. Therefore, it has high accuracy of pattern recognition and function approximation. The simulation indicates the validity of the proposed method of transient stability prediction.关键词
电力系统/GPS/预测/暂态稳定/模糊神经网络分类
信息技术与安全科学引用本文复制引用
苏建设,廖培金,周佃民..基于GPS同步量测量的模糊神经网络用于暂态稳定预测研究[J].继电器,2001,29(2):13-15,19,4.
