|国家科技期刊平台
首页|期刊导航|中国电机工程学报|基于多元同步压缩变换的电力系统强迫振荡源定位

基于多元同步压缩变换的电力系统强迫振荡源定位OACSTPCD

Forced Oscillation Source Location in Power Systems Using Multivariate Synchrosqueezing Transform

中文摘要英文摘要

为实现电力系统强迫振荡源的快速、准确定位,该文提出一种基于多元同步压缩变换(multivariate synchrosqueezing transform,MSST)的电力系统强迫振荡源定位方法.该方法首先利用电力系统的广域量测信息构建发电机的多通道量测信息矩阵,采用MSST对多通道量测信息矩阵同步分解得到对应的三维MSST系数矩阵;然后通过能量权重筛选出表征强迫振荡模式的MSST系数矩阵;进一步,构建基于MSST的发电机强迫振荡耗散能量计算模型,通过筛选出的表征发电机强迫振荡模式的MSST系数矩阵计算各发电机的耗散能量;然后,依据所提的强迫振荡源判据,定位出系统的强迫振荡源;最后,通过WECC-179节点测试系统仿真数据和辽宁电网PMU实测数据验证了所提方法的准确性和有效性.

This paper proposes a multivariate synchrosqueezing transform(MS ST)based power system forced oscillation source location(FOSL)method to locate the forced oscillation source using measurement responses.The method uses the measurement responses to form the multi-channel measurement matrix of each generator,and the MS ST is employed to decompose the multi-channel measurement matrix to obtain the MSST coefficient matrix.Further,the MSST coefficient matrix associated with the forced oscillation mode is determined by using the proposed energy weight.Using the determined MSST coefficient matrix associated with the forced oscillation mode,the MSST-based forced oscillation dissipation energy of each generator is calculated and the forced oscillation source can be located via the proposed FOSL criterion.The performance of the proposed MSST-based FOSL method is evaluated by the simulation data of WECC 179-bus test system and the field-measurement PMU data of Liaoning power grid,and the results validate the accuracy and efficiency of the proposed method in FOSL.

姜涛;刘博涵;李雪;陈厚合;李国庆

现代电力系统仿真控制与绿色电能新技术教育部重点实验室(东北电力大学),吉林省 吉林市 132012

动力与电气工程

电力系统强迫振荡振荡源定位多元同步压缩变换耗散能量流

power systemsforced oscillationoscillation source locationmultivariate synchrosqueezing transformdissipation energy flow

《中国电机工程学报》 2024 (001)

46-57,中插4 / 13

国家自然科学基金项目(52377083);国家自然科学基金委-国家电网公司智能电网联合基金项目(U2066208).Project Supported by National Natural Science Foundation of China(52377083);Joint Foundation of Smart Grid of the National Natural Science Foundation of China State Grid Corporation of China(U2066208).

10.13334/j.0258-8013.pcsee.221736

评论