基于监测点数据分析的风电场电压暂降预警研究
柏晶晶1，袁晓冬2，张帅1，柳伟1，陈兵2，顾伟1
1 东南大学 电气工程学院，江苏 南京 210096；
2 江苏省电力公司电力科学研究院，江苏 南京 210036
摘 要：对风电场电压暂降指标进行深入数据挖掘并给出适当预警，可及时发现电网中已存在或潜在的电能质量问题并加以改善。利用改进的AHP法确定电压暂降各个特征量的权重，结合改进的欧氏距离法计算出风电场并网点电压暂降监测数据、自设等级限值以及前一段时间电压暂降均值的距离系数，进而快速准确地对风电场电压暂降干扰的真实水平做出及时预警。通过实例分析，证明了所提方法的实用性和高效率，可将其有效应用于电能质量异常数据预警系统。
关键词：风电场；电压暂降；预警；改进的欧氏距离法
中图分类号：TM614；TM712 文献标识码：A 文章编号：1007-3175(2014)04-0008-04
Research on Early Warning of Wind Farm Voltage Sag Based on Monitored Data Analysis
BAI Jing-jing1, YUAN Xiao-dong2, ZHANG Shuai1, LIU Wei1, CHEN Bin2, GU Wei1
1 School of Electrical Engineering, Southeast University, Nanjing 210096, China;
2 Jiangsu Electric Power Research Institute, Nanjing 210036, China
Abstract: Further mining voltage sag index of wind farm and suitable early warning could make it possible to timely find the existed and potential power quality problems and to give warning prompts. The improved analytic hierarchy process (AHP) was used to determine the different characteristic weights of voltage sag. Combined with the improved Euclidean distance method, this paper calculate voltage sag monitoring data at wind farm grid points and disposed grading limited values and the distance coefficient of early voltage sag mean to carry out early warning quickly and correctly for the real level of voltage sag disturbance of wind farm. The cases analysis verifies that the proposed approach is useful and high efficient and it is possible to timely conduct power quality early warning for abnormal data.
Key words: wind farm; voltage sag; early warning; improved Euclidean distance method
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