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Individual Load Monitoring of Appliances for Home Energy Management System

Maria Criselda B. Loyola, Jeremiah O. Joson, and Lance Bryan D. Salvador
Electrical Engineering, Malayan Colleges Laguna, Cabuyao City, Philippines
Abstract—Home energy management starts with a monitoring system for the user to become aware of how much energy he/she consumes over a period of time and a controlling system that maximizes energy efficiency. There are two methods of load monitoring used in analyzing loads in residential installations and one of them is Intrusive Load Monitoring (ILM). This study was aimed to create an energy management system focusing on individual load monitoring of household appliances through ILM implementation. Wireless network technology was also utilized for data transmission and access, using Raspberry Pi 3B+ and SenseTecnic cloud host. The notification feature of the system, done through a cloud-based communication platform Twilio, is 100% successful in performing its function. Energy consumption behavior model equations for specific types of appliance loads were generated using regression analysis. All equations have relatively good fit, with R squared of 85% - 94%, and low standard error, except for the equation representing the variable load with sporadic consumption pattern. Nonetheless, there is 99% confidence in the accuracy of the energy consumption behavior. On the other hand, electric consumption of the entire smart meter costs PHP34.051 only for a month of operation. This only suggests that the system will not significantly contribute to the entire household electric energy consumption cost. 
 
Index Terms—Energy consumption behavior model, forecasting, intrusive load monitoring, regression analysis, predicted consumption

Cite: Maria Criselda B. Loyola, Jeremiah O. Joson, and Lance Bryan D. Salvador, "Individual Load Monitoring of Appliances for Home Energy Management System," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 9, No. 4, pp. 273-282, July 2020. Doi: 10.18178/ijeetc.9.4.273-282

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
 
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