TY - GEN
T1 - CoNNECT
T2 - ASME 2012 International Mechanical Engineering Congress and Exposition, IMECE 2012
AU - Omitaomu, O. A.
AU - Bhaduri, B. L.
AU - Maness, C. S.
AU - Kodysh, J. B.
AU - Noranzyk, A. M.
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84887302530&partnerID=8YFLogxK
U2 - 10.1115/IMECE2012-86813
DO - 10.1115/IMECE2012-86813
M3 - Conference contribution
AN - SCOPUS:84887302530
SN - 9780791845226
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
SP - 559
EP - 569
BT - Energy
PB - American Society of Mechanical Engineers (ASME)
Y2 - 9 November 2012 through 15 November 2012
ER -