从摩洛哥多个城市收集的高分辨率智能电表负载数据集。

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES
Data in Brief Pub Date : 2025-09-12 eCollection Date: 2025-10-01 DOI:10.1016/j.dib.2025.112067
Mouad Bensalah, Abdellatif Hair, Reda Rabie, Hatim Derrouz
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引用次数: 0

摘要

在这个数据集中,我们提供了通过安装在多个摩洛哥城市的智能电表收集的高分辨率电力消耗数据,特别关注22千伏配电变压器。本研究使用的智能电表具有存储电气参数的特点,数据来自Laayoune、boujour、Marrakech和Foum Eloued的居民区和工业区。该数据集在马拉喀什以10分钟(30分钟)的频率积累,构成了针对每个地区特点量身定制的精确负荷预测模型的颗粒基础。数据集的原始版本和处理版本都是可用的,从而使其对能源管理,负荷预测和智能电网优化专家和研究人员有价值。这些信息可用于研究消费模式,检测异常,并为最佳配电和电网稳定性开发预测模型。此外,还提供了按地理区域和时间段划分的用电量趋势的直观表示,以方便解释和进一步研究使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

High-resolution smart meter load dataset collected from multiple cities in Morocco.

High-resolution smart meter load dataset collected from multiple cities in Morocco.

High-resolution smart meter load dataset collected from multiple cities in Morocco.

High-resolution smart meter load dataset collected from multiple cities in Morocco.

Here in this data set, we are offering high-resolution electric consumption data collected via smart meters installed across multiple Moroccan cities with special focus on 22 kV distribution transformers. The smart meters employed in this study have the feature of storing electric parameters, and the data has been retrieved from residential and industrial regions in Laayoune, Boujdour, Marrakech, and Foum Eloued. The dataset, accumulated at a 10-minute (30-minute) frequency in Marrakech, constitutes the granular foundation for precise load forecasting models tailored to the idiosyncrasies of each region. Raw and processed versions of the dataset are both available, thereby making it a valuable for energy management, load forecasting, and smart grid optimization experts and researchers. The information can be used to study patterns of consumption, detect anomalies, and develop prediction models for the best power distribution and grid stability. Visual representations of trends in electricity consumption by geographic area and time period are also provided to facilitate ease of interpretation and further research use.

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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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