COFACTOR Drammen dataset - 4 years of hourly energy use data from 45 public buildings in Drammen, Norway.

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Synne Krekling Lien, Harald Taxt Walnum, Åse Lekang Sørensen
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Abstract

To limit energy consumption and peak loads with increased electrification of our society, more information is needed about the energy use in buildings. This article presents a data set that contains 4 years (Jan. 2018- Dec. 2021/Mar. 2022) of hourly measurements of energy and weather data from 45 public buildings located in Drammen, Norway. The buildings are schools (16), kindergartens (20), nursing homes (7) and offices (2). For each building, the data set contains contextual data about the buildings including their floor area, construction year, energy label, information about their heating system and ventilation system in addition to time series data of energy use and weather data. For some of the buildings, the energy measurements only contain measurements of hourly imported electricity, while the time series data for other buildings have submeters for different energy services and technologies. Researchers, energy analysts, building owners and policy makers can benefit from the dataset for e.g. hourly load disaggregation, forecasting of energy loads and flexibility, grid planning and modelling activities.

Abstract Image

Abstract Image

Abstract Image

COFACTOR Drammen数据集-挪威Drammen 45座公共建筑4年来每小时的能源使用数据。
随着社会电气化程度的提高,为了限制能源消耗和高峰负荷,我们需要更多关于建筑物能源使用的信息。本文提供了一个包含4年(2018年1月至2021年12月/ 3月)的数据集。2022年)对挪威德拉门45座公共建筑每小时的能源和天气数据进行测量。这些建筑分别是学校(16座)、幼儿园(20座)、养老院(7座)和办公室(2座)。对于每座建筑,数据集包含建筑的背景数据,包括建筑面积、建筑年份、能源标签、供暖系统和通风系统信息,以及能源使用和天气数据的时间序列数据。对于一些建筑物,能源测量只包含每小时进口电力的测量,而其他建筑物的时间序列数据则包含不同能源服务和技术的子表。研究人员、能源分析师、建筑业主和政策制定者可以从数据集中受益,例如每小时负荷分解、能源负荷和灵活性预测、电网规划和建模活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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