Learning about performance of building systems and facility operations through a capstone project course

Miguel Mora, Semiha Ergan, Hanzhi Chen, Hengfang Deng, An Lei Huang, Jared Maurer, Nan Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Monitoring and analysis of energy consumption and performance of heating ventilation air conditioning (HVAC) systems in facilities can give insights about building behaviors for improving facility operations. However, due to the custom sensor infrastructure needed to monitor building performance parameters, additional costs would be incurred by owners to instrument facilities and their systems. Detailed analysis of building performance in highly sensed facilities can give insights about the behavior of similar facilities that have no budget to have such sensing infrastructure. This paper provides the analysis of energy consumption and HVAC performance data acquired in a minute interval in a highly sensed building through the comparison of several data mining algorithms, such weighted least square linear regression, random forest and K-nearest neighbor. The findings include the performance of such algorithms in identifying patterns and give insights about suitability of such algorithms in predicting the energy use and system performance in similar buildings with no sensor infrastructure.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering
EditorsWilliam J. O'Brien, Simone Ponticelli
PublisherAmerican Society of Civil Engineers (ASCE)
Pages305-312
Number of pages8
EditionJanuary
ISBN (Electronic)9780784479247
DOIs
StatePublished - 2015
Event2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015 - Austin, United States
Duration: Jun 21 2015Jun 23 2015

Publication series

NameCongress on Computing in Civil Engineering, Proceedings
NumberJanuary
Volume2015-January

Other

Other2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015
CountryUnited States
CityAustin
Period6/21/156/23/15

Keywords

  • Building behavior
  • Data management
  • Data mining algorithms
  • HVAC
  • Sensor infrastructure

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications

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  • Cite this

    Mora, M., Ergan, S., Chen, H., Deng, H., Huang, A. L., Maurer, J., & Wang, N. (2015). Learning about performance of building systems and facility operations through a capstone project course. In W. J. O'Brien, & S. Ponticelli (Eds.), Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering (January ed., pp. 305-312). (Congress on Computing in Civil Engineering, Proceedings; Vol. 2015-January, No. January). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/9780784479247.038