基于趋势跨度指数的稳态电能质量趋势识别及预警方法

Trend Identification and Early Warning Method for Steady-state Power Quality Based on Trend-span Index

针对传统稳态电能质量分级预警中多以数值大小与设定阈值对比、较少考虑指标长期变化趋势的局限性,提出一种基于趋势跨度指数的稳态电能质量趋势识别与预警方法。首先采用STL(seasonal and trend decomposition using locally weighted regression)分解算法对稳态电能质量指标时间序列进行回归分解,提取趋势分量;其次采用Mann-Kendall检验法识别电能质量指标趋势分量的趋势类型;然后提出趋势跨度指数以量化电能质量指标趋势变化程度,并根据趋势跨度指数的分布特征划分预警等级;最后采用理想解排序法对监测点电能质量恶化风险进行综合评价。将该方法应用于某市稳态电能质量实际监测数据,对监测点各项电能质量指标以及整体电能质量水平进行趋势预警。

A trend identification and early warning method for steady-state power quality(PQ)based on the trend-span index is proposed,aiming at the limitation of the traditional steady-state PQ classification warning,which mostly focuses on the comparison between the numerical value and the threshold and seldom considers the long-term change trend of the indices.Firstly,the STL decomposition algorithm is used to decompose the steady-state PQ index time series to extract the trend components.Secondly,the Mann-Kendall method is used to identify the trend type of the trend components of the PQ index.Thirdly,the trend-span index is proposed to quantify the trend change of the PQ index and the early warning level is divided according to the distribution characteristics of the trend-span indices.Finally,the ideal solution sorting method is used to comprehensively evaluate the risks of the PQ deterioration at the monitoring sites.The method is applied to the actual monitoring data of the steady-state PQ in a city.The trend warning of various PQ indices and the overall power quality level of monitoring sites is carried out.