摘要
为了实时远程地监测负荷运转状态和识别负荷种类,设计了一种非侵入式负荷监测系统,并研究基于PCA和kNN的负荷识别算法。在电力供给入口端,通过在负荷回路中串联康铜电阻采样工作电流,通过电阻分压网络采样工作电压,并计算负荷的实时有功功率,以1 Hz频率向云服务器发送功率信息。在云服务器端,通过PCA对功率值序列进行特征提取和降维,通过kNN对当前接入的负荷进行归类,用户可以通过终端设备访问负荷监控界面。在实验中,将系统安装于墙壁插座上,对8类家用负荷进行监控和识别,多次实验结果显示负荷平均识别率达到98%以上,验证了该方案的准确性和可行性。
In order to monitor the load′s running condition and identify the load′s type in real time and long distance,a non-intrusive load monitoring system and a load identification algorithm based on PCA and kNN are designed and developed.On the side of power supply inlet,operating current is sampled through putting a series constantan resistor in the load circuit and operating voltage is sampled through a resistive subdivision network.Thus the load′s real-time active power is calculated and uploaded to the cloud server on the frequency of 1 Hz.On the side of cloud server,features extraction and dimensionality reduction are processed by PCA.The running load is classified by kNN.Users can visit the load monitoring interface by terminal devices.In the experiments,the system is installed in the wall socket to monitor and identify eight types of household appliances.Multiple experimental results show that the average rate of identification is above 98%,which verifies that the method proposed is accurate and feasible.
作者
陈彭鑫
仲思东
Chen Pengxin;Zhong Sidong(School of Electronic Information,Wuhan University,Wuhan 430079,China;National Key Laboratory of Surveying and Mapping of Remote Sensing Information Engineering,Wuhan University,Wuhan 430079,China)
出处
《电子技术应用》
2018年第9期91-95,共5页
Application of Electronic Technique
基金
国家测绘地理信息公益性行业科研专项项目(201412015)
