Skip to main content
SHARE
Publication

CoNNECT: Data Analytics for Energy Efficient Communities...

by Olufemi A Omitaomu, Budhendra L Bhaduri, Christopher S Maness, Jeffrey B Kodysh, Amanda M Noranzyk
Publication Type
Conference Paper
Publication Date
Page Numbers
1 to 11
Volume
N/A
Conference Name
2012 ASME International Mechanical Engineering Congress and Exposition
Conference Location
Houston, Texas, United States of America
Conference Sponsor
American Society of Mechanical Engineers
Conference Date
-

Energy efficiency is the lowest cost option being promoted for achieving a sustainable energy policy. Thus, there have been some innovations to reduce residential and commercial energy usage. There have also been calls to the utility companies to give customers access to timely, useful, and actionable information about their energy use, in order to unleash additional innovations in homes and businesses. Hence, some web-based tools have been developed for the public to access and compare energy usage data. In order to advance on these efforts, we propose a data analytics framework called Citizen Engagement for Energy Efficient Communities (CoNNECT).
On the one hand, CoNNECT will help households to understand (i) the patterns in their energy consumption over time and how those patterns correlate with weather data, (ii) how their monthly consumption compares to other households living in houses of similar size and age within the same geographic areas, and (iii) what other customers are doing to reduce their energy consumption. We hope that the availability of such data and analysis to the public will facilitate energy efficiency efforts in residential buildings. These capabilities formed the public portal of the CoNNECT framework. On the other hand, CoNNECT will help the utility companies to better understand their customers by making available to the utilities additional datasets that they naturally do not have access to, which could help them develop focused services for their customers. These additional capabilities are parts of the utility portal of the CoNNECT framework.
In this paper, we describe the CoNNECT framework, the sources of the data used in its development, the functionalities of both the public and utility portals, and the application of empirical mode decomposition for decomposing usage signals into mode functions with the hope that such mode functions could help in clustering customers into unique groups and in developing guidelines for energy conservation.