Abstract
The research paper proposes the methodology of extracting knowledge about the similarity of a certain building’s or construction’s day energy consumption profiles. The methodology is based on the methods of mathematical statistics. With its help distinguishing of the days in the object’s explored past that have the profiles similar to the target day becomes possible. The researcher proposes hypotheses on other features resembling the target day, except for the energy consumption profiles. Having assumed the reasons of the profiles’ repetition and distinguished the days consolidated by a certain feature, with the help of the methodology the researcher can verify whether these days are dominating in the set. The acquired knowledge – the set of accepted or rejected hypotheses about the similarity/difference of the past days compared with the target one – allows to identify hidden patterns in the object’s energy consumption. They significantly facilitate the important tasks of forecasting, identifying the outliers and managing the energy consumption.
The methodology can be applied to the analysis of buildings and constructions of various functional and typological groups, working by “day/night” mode. The practical aspects of the methodology’s application are illustrated with examples, based on the EcoSCADA data.
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Acknowledgments
The work has been done in the framework of grant # RFBR 16-37-00387. The reported study was partially supported by RFBR research projects 16-37-60066 mol a dk, and project MD-6964.2016.9.
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Janovsky, T., Kirichuk, A., Tyukov, A., Shcherbakov, M., Sokolov, A., Brebels, A. (2017). The Technique of Extracting Knowledge About Buildings’ and Constructions’ Day Energy Consumption Models. In: Kravets, A., Shcherbakov, M., Kultsova, M., Groumpos, P. (eds) Creativity in Intelligent Technologies and Data Science. CIT&DS 2017. Communications in Computer and Information Science, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-65551-2_32
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DOI: https://doi.org/10.1007/978-3-319-65551-2_32
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