NILM非侵入式负荷识别（papers with code、data）带代码的论文整理——(公开数据集、工具、和性能指标篇) 全网最全

说在最前面

这篇文章主要介绍用于非侵入式负荷识别领域目前的公开数据集、工具和其它等，如果需要看论文及具体代码实现，看我上一篇的文章。

其外，不是所有数据集我都用过，我只用过UK-DALE。我会在下面标注几个最常用常见的

更新时间：2023年1月10日 21:55:40

公开数据集：

1.REDD（The Reference Energy Disaggregation Data Set） （常用）

http://redd.csail.mit.edu/

id:redd

password:disaggregatetheenergy

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2.AMPds                                                                               （常用）

AMPds (The Almanac of Minutely Power Dataset).

nilmtk自带的converter是对应 AMPds R2013版本

除此之外还有

AMPds2: The Almanac of Minutely Power dataset (Version 2)

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3.CER_Electricity_Data

ISSDA | Commission for Energy Regulation (CER)

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4.Umass Smart Data Set

Smart - UMass Trace Repository

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5.REFIT                                                                    （常用）

颗粒度最细,8s级别

REFIT: Electrical Load Measurements — University of Strathclyde

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6.ENLITEN

https://researchportal.bath.ac.uk/en/datasets/enliten-a-dataset-and-its-associated-analysis-code-for-the-paper

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7.GREEND

GREEND download | SourceForge.net

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8.ElectricityLoadDiagrams

OEDI: Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States

没有missing point

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9.UK-DALE                 （常用）

UK Domestic Appliance-Level Electricity (UK-DALE) dataset | Jack Kelly

https://data.ukedc.rl.ac.uk/browse/edc/efficiency/residential/EnergyConsumption/Domestic

有三个版本

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10.ECO data set 

DSG - Research Project: ECO data set

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11.HES（Household Electricity Study）

Science Search

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 12.The tracebase data set

GitHub - areinhardt/tracebase: The tracebase appliance-level power consumption data set

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13.ENERTALK

https://www.nature.com/articles/s41597-019-0212-5

预处理和可视化代码：GitHub - ch-shin/ENERTALK-dataset: The ENERTALK Dataset, 15 Hz Electricity Consumption Data from 22 Houses in Korea

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14.BLUED

非侵入式负荷分解之BLUED数据集_Alex Ching Ho的博客-CSDN博客_blued数据集

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15.DEDDIAG

DEDDIAG, a domestic electricity demand dataset of individual appliances in Germany

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16.PLAID                                                       （常用）

PLAID2018: PLAID 2018

PLAID 2017:  PLAID 2017

PLAID 2014:  PLAID 2014

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17.MORED: A Moroccan Buildings’ Electricity Consumption Dataset

https://github.com/MOREDataset/MORED

paper:https://www.mdpi.com/1996-1073/13/24/6737

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18.Residential Power Traces for Five Houses: the iHomeLab RAPT Dataset

paper: Data | Free Full-Text | Residential Power Traces for Five Houses: The iHomeLab RAPT Dataset

pre-process code: https://github.com/ihomelab/RAPT-dataset

dataset: Residential Power Traces for Five Houses: the iHomeLab RAPT Dataset | Zenodo

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19.FIRED: A Fully-labeled hIgh-fRequency Electricity Disaggregation Dataset

paper: FIRED | Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation

code: GitHub - voelkerb/FIRED_dataset_helper: Files to load and use the Fully-labeled hIgh-fRequencyElectricity Disaggregation (FIRED) dataset. Files to generate statistics and plots.

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20.RAE:The Rainforest Automation Energy Dataset for Smart Grid Meter Data Analysis

pdf: Data | Free Full-Text | RAE: The Rainforest Automation Energy Dataset for Smart Grid Meter Data Analysis

GitHub - smakonin/RAE.dataset: Scripts of the the Rainforest Automation Energy Dataset (RAE dataset)

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21.COOLL:Controlled On/Off Loads Library, a Public Dataset of High-Sampled Electrical Signals for Appliance Identification

链接无。

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合成数据集：

顾名思义，这里面的电力数据是人工合成的，跟上面用电表仪器采集的数据不一样，这里一般用来做增强数据集。

1.SHED

A Simulated High-frequency Energy Disaggregation dataset for commercial buildings

SHED Dataset

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2.SynD（A Synthetic Energy Consumption Dataset for NILM）

code: GitHub - klemenjak/SynD: A Synthetic Energy Consumption Dataset for Non-Intrusive Load Monitoring

pdf: A synthetic energy dataset for non-intrusive load monitoring in households | Scientific Data

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3.SmartSim

A Device Accurate Smart Home Simulator for Energy Analytics

GitHub - sustainablecomputinglab/smartsim

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4.Device-Free User Activity Detection using Non-Intrusive Load Monitoring: A Case Study

pdf: https://www.areinhardt.de/publications/2020/Reinhardt_DFHS_2020.pdf

code: GitHub - klemenjak/antgen: The AMBAL-based NILM Trace generator (for NILMTK)

How does Load Disaggregation Performance Depend on Data Characteristics? Insights from a Benchmarking Study. (2020).  PDF: https://www.areinhardt.de/publications/2020/Reinhardt_eEnergy_2020.pdf

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工具（框架、数据集转换工具等）：

NILM-TK是一个非侵入式负载监测的开源工具包，专门设计用于以可再现的方式比较能量分解算法，就是Jack Kelly他们几个做的一个toolkit工具包。

论文地址： NILMTK | Proceedings of the 5th international conference on Future energy systems

NILMTK:

Code:  GitHub - nilmtk/nilmtk: Non-Intrusive Load Monitoring Toolkit (nilmtk)

Documentation: NILMTK Documentation

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all the state-of-the-art algorithms for the task of energy disaggregation

GitHub - nilmtk/nilmtk-contrib

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An evaluation framework for non-intrusive load monitoring algorithms

https://github.com/beckel/nilm-eval

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NILM评价指标的相关论文

《On Metrics to Assess the Transferability of Machine Learning Models in Non-Intrusive Load Monitoring》

《Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation,Artificial Intelligence Review》

NILM中的特征选择相关论文

《Comprehensive feature selection for appliance classification in NILM》

DOI：10.1016/j.enbuild.2017.06.042

code:https://github.com/18D070001/Electrical-Devices-Identification-Model

NILM一些拓展应用：

监测独居老人：

《Assessing Human Activity in Elderly People Using Non-Intrusive Load Monitoring》

DOI：10.3390/s17020351

Sustainable Homecare Monitoring System by Sensing Electricity Data | IEEE Journals & Magazine | IEEE Xplore

用NILM实现居家活动的识别：

采样频率对应不同的谐波特征

Non-Intrusive Load Monitoring and Classification of Activities of Daily Living Using Residential Smart Meter Data | IEEE Journals & Magazine | IEEE Xplore

关于NILM的一些网站（workshop、协会之类的）

The International Workshop on Non-Intrusive Load Monitoring (NILM)

http://www.nilm.eu/

http://wiki.nilm.eu/