期刊文献+

基于长短期记忆网络的电网同调机群快速辨识 被引量:3

A Fast Prediction Method of Coherent Generators Based on Long Short-term Memory Network
下载PDF
导出
摘要 基于长短期记忆网络(Long short-term memory,LSTM)提出了一种电网同调机群的快速辨识方法。首先针对两机振荡模型,挖掘相量平面内电压相量轨迹的分类特性,为机组的同调性辨识提供了依据;其次,基于短时响应数据,利用LSTM分别对机端电压实、虚部时序轨迹进行预测,并依据复合而成的相量轨迹判断机组的分群情况;最后,利用扩展等面积法则(Extended equal area criterion,EEAC)对上述分群情况进行验证,进而给出同调机群的最终辨识结果。IEEE-39节点系统算例验证了方法的有效性,具有较好的工程应用价值。 Based on the long short-term memory network(LSTM),a fast prediction method of coherent generators is proposed.Firstly,the classification characteristics of bus voltage phase trajectories are extracted to provide a new way for the identification of generator coherency.Secondly,based on the short-term response data,the real and imaginary parts of the generator terminal voltage phase are predicted respectively by using LSTM,and the coherent generators are identified based on the fitted voltage phase trajectories.Finally,the extended equal area criterion(EEAC)is used to further verify the coherency of the identified generator groups.The proposed method is validated used in the IEEE-39 bus system,and the simulation results show that the method has the advantages of higher engineering practice value.
作者 毛煜 尚海昆 于卓琦 MAO Yu;SHANG Haikun;YU Zhuoqi(School of Electrical Engineering,Northeast Electric Power University,Jilin 132012;State Grid Zhejiang Hangzhou Fuyang Power Supply Company Co.,Ltd.,Hangzhou 311400)
出处 《电气工程学报》 CSCD 2022年第2期201-207,共7页 Journal of Electrical Engineering
关键词 同调机群辨识 电压相量轨迹 长短期记忆网络(LSTM) 扩展等面积法则(EEAC) Coherent generator identification voltage phase trajectory long short-term memory network(LSTM) extended equal area criteria(EEAC)
  • 相关文献

参考文献16

二级参考文献186

共引文献330

同被引文献33

引证文献3

二级引证文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部