基于标幺化三阈值事件检测与LDA分类器的工商业负荷辨识方法

非侵入式负荷辨识技术能够低成本的获取用户各类设备使用情况，实现电力负荷的在线监测与分析，对支撑负荷预测、需求响应等应用开展有着重要意义。针对一般工商业用户类型多样、负荷种类繁多、设备运行特性复杂的特点，提出了一种基于标幺化三阈值事件检测与LDA分类器的工商业负荷辨识方案。首先针对不同能耗级别、不同启停特性的设备设计了参数可调的统一负荷事件检测框架，提升了缓变型、分段型、震荡型负荷事件的检出准确度。随后提出了基于多元特征与LDA线性判别的设备类型判断算法，在兼顾边缘端计算效率的同时取得了与随机森林等非线性分类器相同的辨识性能。

Industrial and commercial load identification method based on normalized three threshold event detection and LDA classifier

Non-intrusive load identification technology can obtain the usage of various equipment at low cost,and can monitor and analyze power load on line,which is of great significance for load forecasting,demand response and other applications. In view of the diversity of general industrial and commercial users,the variety of loads and the complexity of equipment operation characteristics,anindustrial and commercial load identification scheme based on normalized three threshold event detection and LDA classifier is proposed,Firstly,a unified load event detection framework with adjustable parameters is designed for devices with different energy levels and different start-stop characteristics,which improves the detection accuracy of slow-moving,segmented and oscillating load events. Then an equipment type identification algorithm based on multivariate features and LDA linear discrimination is proposed,which achieves the same identification performance as nonlinear classifiers such as random forest while ensuring the computational efficiency of the edge.