TY - GEN
T1 - A BIM-enabled platform for power consumption data collection and analysis
AU - Chiang, C. T.
AU - Ho, T. W.
AU - Chou, C. C.
N1 - Publisher Copyright:
© 2015 ASCE.
PY - 2015
Y1 - 2015
N2 - Comprehensive analysis of power consumption data for assorted home appliances or electrical devices can help identify a household's electricity usage patterns as well as provide potential energy saving suggestions. Currently, modern metering techniques, such as smart meters, non-intrusive load monitoring, and Wi-Fi smart power outlets, can be used to collect the power consumption data in a timely and effective way. However, the data collected have not been analyzed in the context of the encompassing building, which certainly affects its energy use requirements such as heating and cooling. In addition, past research has showed that behavioral interventions are necessary to encourage a resident to save his or her utility bills, which requires disclosure of a household's and the neighbors' electricity usage patterns for comparison. Such the behavioral approaches have been successfully utilized by companies like Opower; nevertheless, they might invade one's privacy if not properly managed. Thus, this research aimed at development of data fusion platforms with capability not only to integrate the power consumption data with the building data from a building information modeling (BIM) tool, but also to protect residents' privacy concerns regarding their electricity usage patterns. Research work includes: (1) development of a tool to automatically transform a Revit file into Unity3D so that residents can see when and where the power is consumed and potential energy saving suggestions in a more interactive way; (2) development of a local platform, called local Real-Time Replay Platform (RTRP), to call a BIM-based energy analysis tool, Ecotect, to create the energy use baselines for residents for comparison; (3) development of a central platform, called central RTRP, to receive the aggregated power consumption data from several local RTRPs of different households so as to compile the neighborhood energy use baselines for all residents to compare with. Preliminary results are presented with research conclusions and future work discussions.
AB - Comprehensive analysis of power consumption data for assorted home appliances or electrical devices can help identify a household's electricity usage patterns as well as provide potential energy saving suggestions. Currently, modern metering techniques, such as smart meters, non-intrusive load monitoring, and Wi-Fi smart power outlets, can be used to collect the power consumption data in a timely and effective way. However, the data collected have not been analyzed in the context of the encompassing building, which certainly affects its energy use requirements such as heating and cooling. In addition, past research has showed that behavioral interventions are necessary to encourage a resident to save his or her utility bills, which requires disclosure of a household's and the neighbors' electricity usage patterns for comparison. Such the behavioral approaches have been successfully utilized by companies like Opower; nevertheless, they might invade one's privacy if not properly managed. Thus, this research aimed at development of data fusion platforms with capability not only to integrate the power consumption data with the building data from a building information modeling (BIM) tool, but also to protect residents' privacy concerns regarding their electricity usage patterns. Research work includes: (1) development of a tool to automatically transform a Revit file into Unity3D so that residents can see when and where the power is consumed and potential energy saving suggestions in a more interactive way; (2) development of a local platform, called local Real-Time Replay Platform (RTRP), to call a BIM-based energy analysis tool, Ecotect, to create the energy use baselines for residents for comparison; (3) development of a central platform, called central RTRP, to receive the aggregated power consumption data from several local RTRPs of different households so as to compile the neighborhood energy use baselines for all residents to compare with. Preliminary results are presented with research conclusions and future work discussions.
UR - http://www.scopus.com/inward/record.url?scp=84936861723&partnerID=8YFLogxK
U2 - 10.1061/9780784479247.012
DO - 10.1061/9780784479247.012
M3 - 會議論文篇章
AN - SCOPUS:84936861723
T3 - Congress on Computing in Civil Engineering, Proceedings
SP - 90
EP - 98
BT - Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering
A2 - O'Brien, William J.
A2 - Ponticelli, Simone
PB - American Society of Civil Engineers (ASCE)
Y2 - 21 June 2015 through 23 June 2015
ER -
