中国电机工程学报2018，Vol.38Issue(1)：137-147,后插14,12.DOI:10.13334/j.0258-8013.pcsee.162072
基于两阶段支持向量机的电力系统暂态稳定预测及预防控制
Two-stage Support Vector Machines for Transient Stability Prediction and Preventive Control of Power Systems
摘要
Abstract
This paper focused on the data driven transient stability analysis of power systems. Considering different requirements of stability analysis and preventive control for input features, and in order to balance the accuracy and transparency of the data mining models, a two-stage support vector machines was presented for transient stability prediction and preventive control. In the first stage, a preventive control model was built using the controllable variables and simple model. In the second stage, a complex but accurate model was built for transient stability prediction. Moreover, the generated preventive control model can also provide a basis for the instance selection for the second stage. The test results show that the proposed prediction model can predict the transient stability accurately and with shorter training time;when the power system is predicted as unstable, preventive control measures can be provided to ensure the security and stability of power system operation.关键词
暂态稳定预测/预防控制/两阶段/支持向量机/特征选择/样本筛选/数据挖掘Key words
transient stability prediction/preventive control/two-stage/support vector machine/feature selection/instance selection/data mining分类
信息技术与安全科学引用本文复制引用
周艳真,吴俊勇,冀鲁豫,于之虹,郝亮亮..基于两阶段支持向量机的电力系统暂态稳定预测及预防控制[J].中国电机工程学报,2018,38(1):137-147,后插14,12.基金项目
国家自然科学基金项目(51577009). Project Supported by National Natural Science Foundation of China (51577009). （51577009）
