Energy Disaggregation via Clustered Regression Models: A Case Study in the Convenience Store

• Main Authors: Hsiao-Hui Chen, 陳孝慧
• Other Authors: Yuh-Jye Lee
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/13386828841973769482

碩士 === 國立臺灣科技大學 === 資訊工程系 === 101 === Global warming and the depletion of natural resources such as oil, coal are some of the most difficult problems we have ever faced. In recent years, people have begun paying more attention to energy saving and environmental issues. Most people do not know what percentage of power consumption was cost in what usage so they would misestimate the direction and the effect of conservation. However, the study shows that continuous feedback to the consumers can reduce energy usage by 10-15\% on average. Therefore, energy disaggregation is more and more important to help consumers understand their electricity consumption distribution and let them know the expenses coming from which appliances. After understanding the distribution, consumers can have their plan on how to achieve power saving. In this thesis, we propose a novel framework using the relationships of appliances with each other to accomplish energy disaggregation. It is reasonable and effective because the using behavior of appliances is regular or even becomes a fixed series of procedures sometimes. In our results, we are not only arriving at 80\% ranking value but also reducing the number of smart meters from 14 to 3.