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dc.creatorBaltazar-Cervantes, J. C.en_US
dc.creatorSakurai, Y.
dc.creatorMasuda, H.
dc.creatorFeinauer, D.
dc.creatorLiu, J.
dc.creatorJi, J.
dc.creatorClaridge, D. E.
dc.creatorDeng, S.
dc.creatorBruner, H.
dc.date.accessioned2007-12-01T00:54:33Z
dc.date.available2007-12-01T00:54:33Z
dc.date.issued2007en_US
dc.identifier.otherESL-IC-07-11-23en_US
dc.identifier.urihttp://hdl.handle.net/1969.1/6222
dc.description.abstractAs the energy costs have been increasing the more energy efficient measures have been promoted in the buildings sector, the reliability of energy consumption data has been attracting significant attention. For example, the reliability of the determination of energy savings depends on that of the energy consumption data, which has to be verified before and after any efficiency measure is applied. From other perspective, verifying energy use data on a regular basis would allow the engineers to identify and assess commissioning opportunities confidently. This paper presents the application of an innovative data screening methodology as a data quality control tool for energy consumption data. The methodology has been applied to a large university campus where the monthly energy consumption, of approximately 100 buildings, must be verified. One of the main responsibilities of the Energy Management Office of the university is to provide monthly utility consumption and cost information to accounting for utility billing of individual buildings. The methodology, which is based on the first law of thermodynamics, or energy conservation, has proved to be an effective data quality screening method for verification of metering sensors when heating, cooling and electricity consumption are separately metered in a building. The methodology is anticipated to be suitable for automated application. In some cases, the methodology could also help to rehabilitate energy use data.en_US
dc.publisherEnergy Systems Laboratory (http://esl.tamu.edu)en_US
dc.publisherTexas A&M University (http://www.tamu.edu)en_US
dc.titleExperiences on the Implementation of the 'Energy Balance' Methodology as a Data Quality Control Tool: Application to the Building Energy Consumption of a Large University Campusen_US


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