A Smart Home Energy Management System Using Two-Stage Non-Intrusive Appliance Load Monitoring over Fog-Cloud Analytics Based on Tridium’s Niagara Framework for Residential Demand-Side Management

Yung-Yao Chen; Ming-Hung Chen; Che-Ming Chang; Fu-Sheng Chang; Yu-Hsiu Lin

doi:10.3390/s21082883

Sensors (Apr 2021)

A Smart Home Energy Management System Using Two-Stage Non-Intrusive Appliance Load Monitoring over Fog-Cloud Analytics Based on Tridium’s Niagara Framework for Residential Demand-Side Management

Yung-Yao Chen,
Ming-Hung Chen,
Che-Ming Chang,
Fu-Sheng Chang,
Yu-Hsiu Lin

Affiliations

Yung-Yao Chen: Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei 106335, Taiwan
Ming-Hung Chen: Department of Electrical Engineering, Ming Chi University of Technology, New Taipei City 243303, Taiwan
Che-Ming Chang: Business Development Department, First International Computer, Inc. (FIC), Taipei 11491, Taiwan
Fu-Sheng Chang: Customer Support & RMA Team, First International Computer, Inc. (FIC), Taipei 11491, Taiwan
Yu-Hsiu Lin: Graduate Institute of Automation Technology, National Taipei University of Technology, Taipei 106344, Taiwan

DOI: https://doi.org/10.3390/s21082883
Journal volume & issue: Vol. 21, no. 8
p. 2883

Abstract

Read online

Electricity is a vital resource for various human activities, supporting customers’ lifestyles in today’s modern technologically driven society. Effective demand-side management (DSM) can alleviate ever-increasing electricity demands that arise from customers in downstream sectors of a smart grid. Compared with the traditional means of energy management systems, non-intrusive appliance load monitoring (NIALM) monitors relevant electrical appliances in a non-intrusive manner. Fog (edge) computing addresses the need to capture, process and analyze data generated and gathered by Internet of Things (IoT) end devices, and is an advanced IoT paradigm for applications in which resources, such as computing capability, of a central data center acted as cloud computing are placed at the edge of the network. The literature leaves NIALM developed over fog-cloud computing and conducted as part of a home energy management system (HEMS). In this study, a Smart HEMS prototype based on Tridium’s Niagara Framework® has been established over fog (edge)-cloud computing, where NIALM as an IoT application in energy management has also been investigated in the framework. The SHEMS prototype established over fog-cloud computing in this study utilizes an artificial neural network-based NIALM approach to non-intrusively monitor relevant electrical appliances without an intrusive deployment of plug-load power meters (smart plugs), where a two-stage NIALM approach is completed. The core entity of the SHEMS prototype is based on a compact, cognitive, embedded IoT controller that connects IoT end devices, such as sensors and meters, and serves as a gateway in a smart house/smart building for residential DSM. As demonstrated and reported in this study, the established SHEMS prototype using the investigated two-stage NIALM approach is feasible and usable.

Published in Sensors

ISSN: 1424-8220 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Chemical technology
Website: http://www.mdpi.com/journal/sensors

About the journal

Abstract

Keywords