Abstract Nowadays Non-Intrusive Load Monitoring (NILM) is considered a hot topic among researchers. The energy disaggregation datasets are used as the benchmark to validate the performance of energy disaggregation algorithms. It is indeed rather difficult to record the load monitoring of devices and appliances; therefore various benchmarking datasets have been proposed during the past few years. This paper presentsa comprehensive review of 42 NILM datasets aided by comparison tables, generated to elaborate on the diverse features of existing datasets. Moreover, the strengths and limitations of present NILM datasets are highlighted with an outlook on present challenges and future research directions as a contribution to the field of energy disaggregation and load identification. The review will help the researchers to evaluate the performance of new NILM algorithms. We believe that this work could be served as a guideline and can potentially open new research perspectives to the scientific community working on developing new NILM datasets.

中文翻译：

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对最先进的非侵入式负载监控数据集的批判性审查

摘要 目前，非侵入式负载监测（NILM）被认为是研究人员的热门话题。能量分解数据集被用作验证能量分解算法性能的基准。记录设备和电器的负载监控确实比较困难；因此，在过去几年中提出了各种基准数据集。本文通过比较表对 42 个 NILM 数据集进行了全面审查，这些数据集用于详细说明现有数据集的不同特征。此外，通过对当前挑战和未来研究方向的展望，突出了当前 NILM 数据集的优势和局限性，作为对能量分解和负载识别领域的贡献。该评论将帮助研究人员评估新 NILM 算法的性能。我们相信，这项工作可以作为指导方针，并有可能为致力于开发新 NILM 数据集的科学界开辟新的研究视角。