电网技术
電網技術
전망기술
POWER SYSTEM TECHNOLOGY
2013年
8期
2157-2164
,共8页
宋洪磊%吴俊勇%郝亮亮%冀鲁豫
宋洪磊%吳俊勇%郝亮亮%冀魯豫
송홍뢰%오준용%학량량%기로예
广域量测系统%拉普拉斯特征映射%同调识别%特征提取
廣域量測繫統%拉普拉斯特徵映射%同調識彆%特徵提取
엄역량측계통%랍보랍사특정영사%동조식별%특정제취
wide area measurement system (WAMS)%Laplacian Eigenmap algorithm%coherency identification%feature extraction
当系统发生严重级联故障导致失步运行时,需要快速准确地识别出系统中的同调机群,为下一步的自主解列控制提供基础。针对WAMS测量到的发电机动态轨迹信息往往具有非线性和非平稳性等特点,提出了一种在线识别同调机群的新方法,能充分考虑各种故障场景的动态特性和非线性系统的时变特征。首先根据WAMS量测可得到故障后发电机组的实时响应功角轨迹信息,利用基于类别信息和核空间的改进拉普拉斯特征映射算法提取特征信息,进而识别出各发电机的运行特性;再利用k-way余弦相似度因子分群算法对发电机组进行自主识别分群。最后通过新英格兰39节点系统仿真,验证了所提方法的有效性,并且适用于系统不同运行方式,能在线准确识别同调机群。
噹繫統髮生嚴重級聯故障導緻失步運行時,需要快速準確地識彆齣繫統中的同調機群,為下一步的自主解列控製提供基礎。針對WAMS測量到的髮電機動態軌跡信息往往具有非線性和非平穩性等特點,提齣瞭一種在線識彆同調機群的新方法,能充分攷慮各種故障場景的動態特性和非線性繫統的時變特徵。首先根據WAMS量測可得到故障後髮電機組的實時響應功角軌跡信息,利用基于類彆信息和覈空間的改進拉普拉斯特徵映射算法提取特徵信息,進而識彆齣各髮電機的運行特性;再利用k-way餘絃相似度因子分群算法對髮電機組進行自主識彆分群。最後通過新英格蘭39節點繫統倣真,驗證瞭所提方法的有效性,併且適用于繫統不同運行方式,能在線準確識彆同調機群。
당계통발생엄중급련고장도치실보운행시,수요쾌속준학지식별출계통중적동조궤군,위하일보적자주해렬공제제공기출。침대WAMS측량도적발전궤동태궤적신식왕왕구유비선성화비평은성등특점,제출료일충재선식별동조궤군적신방법,능충분고필각충고장장경적동태특성화비선성계통적시변특정。수선근거WAMS량측가득도고장후발전궤조적실시향응공각궤적신식,이용기우유별신식화핵공간적개진랍보랍사특정영사산법제취특정신식,진이식별출각발전궤적운행특성;재이용k-way여현상사도인자분군산법대발전궤조진행자주식별분군。최후통과신영격란39절점계통방진,험증료소제방법적유효성,병차괄용우계통불동운행방식,능재선준학식별동조궤군。
When power system suffers from cascading failures that would lead to system asynchronous operation, it is necessary to identify coherent generator groups accurately, which supplies basis for the study on controlled islanding strategy. Because dynamic trajectory of generator measured by WAMS tends to have nonlinear and non-stationary characteristic, a novel approach on identification of coherent generator groups is presented. This method can fully consider dynamic behavior of different fault modes and time varying characteristic of nonlinear system. Firstly, the real-time rotor angle trajectory information can be measured by WAMS directly. Based on categorization information and improved Laplacian Eigenmap algorithm in the kernel space, it extracts the feature information and identifies generator operation characteristic. Then with k-way Cosine similarity factor, it can provide automation for identifying coherent generator. Finally, the simulations on New England 39-bus system validate the effectiveness of such the novel approach proposed in this paper,which is suitable for different operation conditions. It can identify coherent generators on-line accurately.