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Non-intrusive load monitoring based on graph signal processing

机译:基于图形信号处理的非侵入式负载监控

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NALM (Non-intrusive Appliance Load Monitoring) is effective method to disaggregate a particular appliance from the aggregate active power measurements acquired from a common measurement point. Based on appliance level energy consumption data optimum energy utilisation can be obtained by formulating load scheduling strategies. Power consumption of an appliance load is smooth and follows a certain pattern, this motivates the use of graph based signal processing (GSP) for NALM. In the presented work we propose a different NALM method by incorporating on GSP, by representing active power dataset on a graph. Proposed regularization method is applied for maximizing the smoothness of the graph signal, which allow us to perform energy disaggregation in simpler manner. Proposed method is evaluated on publically available iAWE dataset.
机译:NALM(非侵入式设备负载监控)是一种有效的方法,可以将特定设备与从一个公共测量点获取的总有功功率测量结果进行分类。基于设备级别的能耗数据,可以通过制定负载调度策略来获得最佳的能源利用率。设备负载的功耗很平稳,并且遵循一定的模式,这激发了针对NALM使用基于图形的信号处理(GSP)的动机。在提出的工作中,我们通过结合在GSP上,通过在图形上表示有功功率数据集,提出了一种不同的NALM方法。提出的正则化方法用于最大化图形信号的平滑度,这使我们能够以更简单的方式执行能量分解。建议的方法将在可公开获得的iAWE数据集上进行评估。

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