Department of Information Technology, Ghent University - imec, Technologiepark-Zwijnaarde 126, 9052, Ghent, Belgium.
Civil & Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213-3890, United States.
Sci Data. 2020 Feb 12;7(1):49. doi: 10.1038/s41597-020-0389-7.
This paper presents the Plug-Load Appliance Identification Dataset (PLAID), a labelled dataset containing records of the electrical voltage and current of domestic electrical appliances obtained at a high sampling frequency (30 kHz). The dataset contains 1876 records of individually-metered appliances from 17 different appliance types (e.g., refrigerators, microwave ovens, etc.) comprising 330 different makes and models, and collected at 65 different locations in Pittsburgh, Pennsylvania (USA). Additionally, PLAID contains 1314 records of the combined operation of 13 of these appliance types (i.e., measurements obtained when multiple appliances were active simultaneously). Identifying electrical appliances based on electrical measurements is of importance in demand-side management applications for the electrical power grid including automated load control, load scheduling and non-intrusive load monitoring. This paper provides a systematic description of the measurement setup and dataset so that it can be used to develop and benchmark new methods in these and other applications, and so that extensions to it can be developed and incorporated in a consistent manner.
本文介绍了 Plug-Load Appliance Identification Dataset（PLAID），这是一个包含家庭电器电压和电流记录的标记数据集，是在高采样频率（30kHz）下获得的。该数据集包含了来自 17 种不同电器类型（如冰箱、微波炉等）的 1876 个单独计量电器的记录，包括 330 种不同的品牌和型号，采集自美国宾夕法尼亚州匹兹堡的 65 个不同地点。此外，PLAID 还包含了 13 种这些电器类型同时运行的 1314 个记录（即当多个电器同时运行时获得的测量结果）。基于电测量来识别电器对于电力电网的需求侧管理应用非常重要，包括自动负载控制、负载调度和非侵入式负载监测。本文提供了测量设置和数据集的系统描述，以便可以将其用于开发和基准测试这些和其他应用中的新方法，并且可以以一致的方式对其进行扩展和整合。
