Embedded NILM as Home Energy Management System: A Heterogeneous Computing Approach

被引：0

作者：

Deluno Garcia F. ^{[1
]}

Angelino De Souza W. ^{[2
]}

Pinhabel Marafao F. ^{[1
]}

机构：

[1] Institute of Science and Technology of Sorocaba, São Paulo State University (UNESP), Sorocaba SP

[2] Department of Computer Science, Federal University of São Carlos (UFSCar), Sorocaba SP

来源：

IEEE Latin America Transactions | 2019年 / 18卷 / 02期

关键词：

Cognitive meter; energy management; energy meter; NILM; smart metering;

D O I：

10.1109/TLA.2019.9082249

中图分类号：

学科分类号：

摘要：

This paper presents an embedded NILM engine to enable load disaggregation intelligence and explore its potential application as an energy management system. In this sense, the power meter is upgraded to a novel category called cognitive power meter. Therefore, this paper discloses a heterogeneous multiprocessing approach to attend NILM prerequisites and increase household interactivity. The proposed NILM performs the microscopic analysis using the Conservative Power Theory (CPT) for feature extraction; k-Nearest Neighbors (k-NN) for the appliance classification; and the Power Signature Blob (PSB) for energy disaggregation. Results show NILM can be performed on-site, embedded into modern cognitive power meters, and it may support households on providing valuable information concerning appliances' usage for energy management systems. © 2003-2012 IEEE.

引用

页码：360 / 367

页数：7

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