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Load recognition for different loads with the same real power and reactive power in a non-intrusive load-monitoring system

机译:在非侵入式负载监控系统中,具有相同有功功率和无功功率的不同负载的负载识别

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This paper proposes the use of power signature to recognize different loads with the same real power and reactive power in a non-intrusive load-monitoring (NILM) system. To test the performance of the proposed approach, the data sets for electrical loads were analyzed and established using an electromagnetic transient program (EMTP) and onsite load measurement. Load recognition techniques were applied in a neural network. The effectiveness of load recognition and the time requirement were analyzed and compared using a back propagation classifier method. The experiments revealed that analyzing the turn-on transient energy signatures can enhance the efficiency of load recognition, particularly for different loads with the same real power and reactive power in a NILM system, and improve ability of computational speed.
机译:本文提出在非侵入式负载监控(NILM)系统中使用功率签名来识别具有相同有功功率和无功功率的不同负载。为了测试所提出方法的性能,使用电磁暂态程序(EMTP)和现场负载测量来分析和建立电负载数据集。负载识别技术已应用于神经网络。使用反向传播分类器方法对负载识别的有效性和时间要求进行了分析和比较。实验表明,分析打开的瞬态能量特征可以提高负载识别的效率,特别是对于NILM系统中具有相同有功功率和无功功率的不同负载,并可以提高计算速度。

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