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Electricity consumption pattern disaggregation using non-intrusive appliance load monitoring method

机译:使用非侵入式设备负荷监控方法的用电模式分类

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摘要

In practice, a standard energy meter can only capture the overall electricity consumption and estimating electricity consumption pattern of various appliances from the overall consumption pattern is complicated. Therefore, the Non-Intrusive Appliance Load Monitoring (NIALM) technique can be applied to trace electricity consumption from each appliance in a monitored building. However, the method requires a detailed, second-by-second power consumption data which is commonly not available without the use of high specification energy meter. Hence, this paper analyzes the impact of different time sampling data in estimating the energy consumption pattern of various appliances through NIALM method. This is so that consumers will have an overview of time sampling data which is required in order to apply the NIALM technique. As for the analysis, air-conditioning systems and fluorescent lamps were used in the experimental setup. One minute sample rate was the minimum time interval required by NIALM carried out in this analysis. Through the study presented in this paper, it can be established that higher time sampling led to uncertain appliance detection and low accuracy.
机译:在实践中,标准电表只能捕获总体用电量,并且从总体用电量模式估计各种电器的用电量模式很复杂。因此,可以将非侵入式设备负载监控(NIALM)技术应用于跟踪受监控建筑物中每个设备的用电量。但是,该方法需要详细的每秒功耗数据,如果不使用高规格电表通常是无法获得的。因此,本文分析了不同时间采样数据对通过NIALM方法估算各种电器的能耗模式的影响。这样一来,消费者便可以了解应用NIALM技术所需的时间采样数据概览。至于分析,在实验装置中使用了空调系统和荧光灯。一分钟采样率是NIALM在此分析中所需的最小时间间隔。通过本文中的研究,可以确定较长时间的采样导致不确定的设备检测和较低的准确性。

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