Short-term load forecasting data with hierarchical advanced metering infrastructure and weather features
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资源简介：
Accurate short-term load forecasting (STLF) plays an increasingly important role in reliable and economical power system operations. This dataset contains The University of Texas at Dallas (UTD) campus load data with 13 buildings, together with 20 weather and calendar features. The dataset spans from 01/01/2014 to 12/31/2015 with an hourly resolution. The dataset is beneficial to various research such as STLF.
精确的短期负荷预测（STLF）在确保电力系统可靠和经济运行中扮演着日益重要的角色。本数据集包含德克萨斯大学达拉斯分校（UTD）校园内13座建筑的负荷数据，以及20项天气和日历特征。数据集时间跨度为2014年1月1日至2015年12月31日，具有每小时分辨率。该数据集对短期负荷预测等众多研究领域具有显著价值。
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IEEE Dataport
