引用本文:蒋长江,刘俊勇,刘友波,苟 竞,陈 晨,刘若凡,BAZARGAN Masoud.基于广域测量系统和CELL理论的强迫振荡在线感知与定位[J].电力自动化设备,2015,35(2):
JIANG Changjiang,LIU Junyong,LIU Youbo,GOU Jing,CHEN Chen,LIU Ruofan,BAZARGAN Masoud.Online forced oscillation detection and identification based on wide area measurement system and CELL theory[J].Electric Power Automation Equipment,2015,35(2):
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基于广域测量系统和CELL理论的强迫振荡在线感知与定位
蒋长江1, 刘俊勇1, 刘友波1, 苟 竞1, 陈 晨1, 刘若凡1, BAZARGAN Masoud2
1.四川大学 电气信息学院,四川 成都 610065;2.阿尔斯通电网研究与技术中心,英国 斯塔福德 ST17 4LX
摘要:
为了快速准确地定位电网强迫功率扰动源,根据“先感知,再分类,后定位”的思想,提出基于广域测量系统的空间特征椭球和决策树混合定位扰动源的新方法。通过对比分析不同强迫功率振荡信号,将实测的不同受扰轨迹信息映射到多维特征椭球,通过计算椭球的空间形状及其形态参数变化,实现强迫功率振荡态势的定量化描述;在抽取空间椭球特征参数的基础上,将不同扰动下强迫振荡瞬态阶段的特征椭球参数形成决策树样本集,利用C4.5算法离线训练,在线匹配以快速分类定位扰动源。算例结果表明,该方法可以在强迫功率振荡瞬态阶段快速分类定位不同扰动源,定位振荡主要参与机组和负荷的准确率很高。
关键词:  强迫振荡  扰动源定位  广域测量系统  特征椭球  决策树
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Online forced oscillation detection and identification based on wide area measurement system and CELL theory
JIANG Changjiang1, LIU Junyong1, LIU Youbo1, GOU Jing1, CHEN Chen1, LIU Ruofan1, BAZARGAN Masoud2
1.School of Electrical Engineering and Information,Sichuan University,Chengdu 610065,China;2.ALSTOM Grid Research & Technology Centre,Stafford ST17 4LX,UK
Abstract:
According to the concept of “detection-classification-identification”,a hybrid method applying space CELL(Characteristic ELLipsoid) and decision trees based on the wide area measurement system is proposed to quickly and accurately identify the disturbance source of grid forced power oscillation. Different forced power oscillation signals are compared and the information of different measured perturbed trajectories is mapped to a multi-dimensional CELL. The space of CELL and its shape parameter variation are calculated to realize the quantitative description of forced power oscillation. The characteristic parameters of CELL during the transient phase of forced power oscillation under different disturbances are extracted to form the decision tree set,which is offline trained by C4.5 algorithm and online matched to fast classify and locate the disturbance source. Results of case study show that,the different disturbance sources are quickly classified and identified during the transient phase of forced power oscillation and the main contributing units and loads are identified with very high accuracy.
Key words:  forced oscillation  disturbance source identification  wide area measurement system  characteristic ellipsoid  decision tree

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