Filtered dataset of Irish energy performance certificates: A data-driven approach for enhanced building stock modelling

被引:0
作者
Raushan, Kumar [1 ,2 ,3 ,5 ,6 ]
Uidhir, Tomas Mac [3 ,4 ,6 ]
Salvador, Marisa Llorens [1 ,2 ,3 ]
Norton, Brian [1 ,2 ,3 ,5 ]
Ahern, Ciara [1 ,2 ,3 ,6 ]
机构
[1] Technol Univ Dublin, Dublin Energy Lab, Dublin, Ireland
[2] Technol Univ Dublin, Built Environm Res & Innovat Ctr, Dublin, Ireland
[3] SFI Ctr Energy Climate & Marine, MaREI, Dublin, Ireland
[4] Univ Coll Cork, Environm Res Inst, MaREI Ctr, Energy Policy & Modelling Grp, Lee Rd, Cork, Ireland
[5] Univ Coll Cork, Tyndall Natl Inst, Int Energy Res Ctr, Cork, Ireland
[6] Irish Bldg Stock Observ, Dublin, Ireland
来源
DATA IN BRIEF | 2025年 / 59卷
基金
爱尔兰科学基金会; 英国工程与自然科学研究理事会;
关键词
Energy performance certificates; Data validation; Data-driven statistical methods; Dwelling energy assessment procedure; EPC database; Building energy rating; Irish housing stock;
D O I
10.1016/j.dib.2025.111281
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The data presented in this article supports the research publication "A data-driven standardised generalisable methodology to validate a large energy performance Certification dataset: A case of the application in Ireland" by Raushan et al. [1]. It provides the filtered Energy Performance Certificate (EPC) database for residential buildings in Ireland after applying rigorous data validation methods to remove erroneous entries, and outliers. EPCs contain valuable information about building energy efficiency and characteristics. The raw EPC database for Ireland is publicly accessible but contains over 1 million unfiltered entries with inconsistent and erroneous values that can skew analysis. This processed dataset enhances the quality and robustness of the EPC data for use in building stock modelling and research. The data is openly available in .CSV format along with the methodology used for processing the raw database, published in full Python scripts. Supporting notes and metadata explain the filtering process, experimental design, and content of 211 variables across four categories: Informational, form, envelope, and system. By publishing this standardised data- driven filtered EPC dataset, this research enables stakeholders, non-expert and expert alike, to leverage this higher quality input for characterising the Irish housing stock. (c) 2025 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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页数:9
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