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Open AccessArticle

A Household Energy Efficiency Index Assessment Method Based on Non-Intrusive Load Monitoring Data

1
Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
2
Tianjin Electric Power Research Institute, State Grid Tianjin Electric Power Company, Tianjin 300384, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2020, 10(11), 3820; https://doi.org/10.3390/app10113820
Received: 22 April 2020 / Revised: 27 May 2020 / Accepted: 27 May 2020 / Published: 30 May 2020
(This article belongs to the Special Issue Energy-efficient Internet of Things (IoT))
Various countries in the world are vigorously developing energy-saving industries and attaching importance to the improvement of household energy efficiency, but it is difficult to evaluate user power consumption characteristics due to insufficient information and large data granularity. It is, however, possible to evaluate the energy efficiency of household users via non-intrusive load monitoring (NILM). This paper explores the energy efficiency assessment of residential users and proposes a household energy efficiency assessment method based on NILM data. An energy efficiency assessment index of residents is provided by analyzing factors that affect residents’ energy efficiency. This index is clear, operable, and easy to obtain and quantify. Based on NILM information, clustering, and comprehensive evaluation, as well as combining the entropy weight method with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), a user’s energy efficiency can be evaluated and analyzed. Some case studies are provided to verify the validity of the proposed method based on non-intrusive information, to analyze the characteristics and deficiencies of the user’s energy consumption, and to give corresponding energy recommendations. View Full-Text
Keywords: energy efficiency assessment; NILM; resident users; clustering analysis; TOPSIS energy efficiency assessment; NILM; resident users; clustering analysis; TOPSIS
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MDPI and ACS Style

Kong, X.; Zhu, S.; Huo, X.; Li, S.; Li, Y.; Zhang, S. A Household Energy Efficiency Index Assessment Method Based on Non-Intrusive Load Monitoring Data. Appl. Sci. 2020, 10, 3820. https://doi.org/10.3390/app10113820

AMA Style

Kong X, Zhu S, Huo X, Li S, Li Y, Zhang S. A Household Energy Efficiency Index Assessment Method Based on Non-Intrusive Load Monitoring Data. Applied Sciences. 2020; 10(11):3820. https://doi.org/10.3390/app10113820

Chicago/Turabian Style

Kong, Xiangyu; Zhu, Shijian; Huo, Xianxu; Li, Shupeng; Li, Ye; Zhang, Siqiong. 2020. "A Household Energy Efficiency Index Assessment Method Based on Non-Intrusive Load Monitoring Data" Appl. Sci. 10, no. 11: 3820. https://doi.org/10.3390/app10113820

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