详细信息
A novel oscillation identification method for grid-connected renewable energy based on big data technology ( SCI-EXPANDED收录 CPCI-S收录)
文献类型:期刊文献
英文题名:A novel oscillation identification method for grid-connected renewable energy based on big data technology
作者:Wang, Jian[1]
第一作者:王健
通讯作者:Wang, J[1]
机构:[1]Henan Univ Econ & Law, Zhengzhou, Peoples R China
第一机构:河南财经政法大学
通讯机构:[1]corresponding author), Henan Univ Econ & Law, Zhengzhou, Peoples R China.|[10484]河南财经政法大学;
年份:2022
卷号:8
起止页码:663-671
外文期刊名:ENERGY REPORTS
收录:;WOS:【SCI-EXPANDED(收录号:WOS:000770814900063),CPCI-S(收录号:WOS:000770814900063)】;
基金:The research is supported by the science and technology research project of science and technology department of Henan Province, China (No. 212102210386).
语种:英文
外文关键词:Oscillation identification; Big data; Evidence theory; Support vector machine
摘要:With the development of big data technology, power system has entered the era of data analysis. With the help of the massive data provided by the wide area measurement system, the power system can be easily evaluated, and the abnormal operation status can be detected and positioned. As the increase of renewable energy permeability, more new abnormal operating status have appeared in the system. Aimed at the abnormal operation state in the development of new energy, this paper proposes an oscillation location scheme based on evidence theory and support vector machine, which makes up for the limitation of single oscillation location method. The result of location analysis of oscillation energy method, oscillation phase difference method and forced oscillation phase difference location method is fused by evidence theory. (C) 2022 The Author(s). Published by Elsevier Ltd.
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