配电物联网电能质量复合扰动检测研究

Research on Power Quality Composite Disturbance Detection in Power Distribution IOT

传统的电能质量复合扰动检测方法无法准确获取电能质量特征,电能数据滤波效果不理想,导致其存在识别率低、检测偏差大和检测效果差的问题。提出配电物联网电能质量复合扰动的检测方法。建立离散非线性系统和强跟踪滤波器,将其应用在配电物联网中,提取电能质量复合扰动特征;选取基波幅值的最大值和最小值、波动次数、渐消因子频度作为扰动特征,并将提取的特征输入支持向量机中,完成配电物联网电能质量复合扰动的检测。实验结果表明,所提方法可有效识别电能质量复合扰动,其检测结果偏差较小,且可精准获取电能质量复合扰动在配电物联网中的发生时刻和结束时刻,验证了所提方法的整体有效性。

The current method for power quality composite disturbance detection cannot accurately obtain the power quality characteristics,and the filtering effect of power data is not ideal,which results in low recognition rate,large detection deviation and poor detection effect. To this end,a composite disturbance detection method for power quality of distribution IOT is proposed in this paper. The discrete nonlinear system and strong tracking filter are established and applied to the distribution Internet of things to extract the characteristics of power quality composite disturbance. The maximum fundamental amplitude, minimum fundamental amplitude,fluctuation times and frequency of the fading factor are selected as disturbance features,and the extracted features are input into the support vector machine to complete the detection of composite disturbance of power quality in distribution Internet of things. The experimental results show that the proposed method can effectively identify the power quality composite disturbance with small detection deviation,and the occurrence time and end time of the power quality composite disturbance in the distribution Internet of things can be accurately obtained,which verifies the overall effectiveness of the proposed method.