基于云模型的电能质量实时状态诊断原理及实现

中文摘要: 提出基于云模型的电能质量实时状态诊断方法，在各监测点长期电能质量监测数据基础上分别对各项电能质量指标建立正态云模型，根据正态云隶属曲线外边界确定异常阈值。实时监测过程中通过电能质量数据与异常阈值比较，判断其是否异常。基于云模型的电能质量实时状态诊断以荷源长期运行特性为基础，能够准确识别出异常电能质量状况，发现潜在的非常态运行问题。实际工程算例说明了提出的方法的实用性和有效性。
Abstract:A method of power quality real-time status diagnosis based on cloud model was proposed.The normal cloud model for each power quality index was established based on long-term power quality data of each monitoring point.The anomaly threshold determined by the normal cloud outline was used to diagnose the power quality status in the process of monitoring.This method can accurately identify the abnormal power quality status,and find out the potential issue of abnormal operation on the basis of long-term operation characteristics of the power grid. Practical engineering example proved the validity and practicality of the proposed method.