论文标题
在非侵入性负载监控中迈向可比性：关于数据和绩效评估
Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance Evaluation
论文作者
论文摘要
非侵入式负载监测（NILM）包括一组技术，这些技术为家庭和工业设施的能源消耗提供了见解。最新贡献显示了准确性和概括能力的显着提高。尽管在分类技术方面取得了所有进展，但绩效评估和可比性仍然是一个开放的研究问题。缺乏标准化和评估程序的共识使可重复性和可比性极为困难。在本文中，我们将注意力集中在尼尔姆的可比性上，重点是强调用于测试算法性能的常见能量数据集之间的巨大差异。我们将有关可比性的讨论分为数据方面，绩效指标，并对评估过程进行仔细观察。发现有关预处理以及数据清洁方法，统一绩效报告的重要性以及对负载分解中的复杂性测量的需求是与NILM相关研究中最紧迫的问题的详细信息。此外，我们的评估表明应仔细选择数据集。我们通过为将来的工作提出建议来提高可比性。
Non-Intrusive Load Monitoring (NILM) comprises of a set of techniques that provide insights into the energy consumption of households and industrial facilities. Latest contributions show significant improvements in terms of accuracy and generalisation abilities. Despite all progress made concerning disaggregation techniques, performance evaluation and comparability remains an open research question. The lack of standardisation and consensus on evaluation procedures makes reproducibility and comparability extremely difficult. In this paper, we draw attention to comparability in NILM with a focus on highlighting the considerable differences amongst common energy datasets used to test the performance of algorithms. We divide discussion on comparability into data aspects, performance metrics, and give a close view on evaluation processes. Detailed information on pre-processing as well as data cleaning methods, the importance of unified performance reporting, and the need for complexity measures in load disaggregation are found to be the most urgent issues in NILM-related research. In addition, our evaluation suggests that datasets should be chosen carefully. We conclude by formulating suggestions for future work to enhance comparability.
