A Workflow Investigating the Information behind the Time-Series Energy Consumption Condition via Data Mining
Auteur(s): |
Xiaodong Liu
Shuming Zhang Weiwen Cui Hong Zhang Rui Wu Jie Huang Zhixin Li Xiaohan Wang Jianing Wu Junqi Yang |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 23 août 2023, n. 9, v. 13 |
Page(s): | 2303 |
DOI: | 10.3390/buildings13092303 |
Abstrait: |
The purpose of this study is to develop a framework to understand building energy usage pattern finding using data mining algorithms. Developing advanced techniques and requirements for carbon emission reduction provides higher demands for building energy efficiency. Research conducted so far has mainly focused on total energy consumption data clusters instead of time-series curve peculiarity. This research adopts the time-series cluster algorithm k-shape and the ARM Apriori method to study the simulation database generated by the official restaurant energy model. These advanced data mining techniques can discover potential information hidden in a big database that has not been identified by people. The results show that the restaurant time-series energy consumption curve can be clustered into four type patterns: Invert U, M, Invert V, and Multiple M. Each mode has its own variation characteristics. Two aspects for the solution of intensity and peak shift are proposed, achieving energy savings and focusing on different curve modes. The conclusion shows that the combination of time-series clustering and the ARM algorithm work flow can successfully discover the building operation pattern. Some solutions focusing on restaurant energy usage issues have been proposed, and future investigations should pay more attention to building area-influenced factors. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10740682 - Publié(e) le:
12.09.2023 - Modifié(e) le:
14.09.2023