LAPSE:2023.26995
Published Article
LAPSE:2023.26995
A Dataset for Non-Intrusive Load Monitoring: Design and Implementation
April 3, 2023
Abstract
A NILM dataset is a valuable tool in the development of Non-Intrusive Load Monitoring techniques, as it provides a means of evaluation of novel techniques and algorithms, as well as for benchmarking. The figure of merit of a NILM dataset includes characteristics such as the sampling frequency of the voltage, current, or power, the availability of indications (ground-truth) of load events during recording, the variety and representativeness of the loads, and the variety of situations these loads are subject to. Considering such aspects, the proposed LIT-Dataset was designed, populated, evaluated, and made publicly available to support NILM development. Among the distinct features of the LIT-Dataset is the labeling of the load events at sample level resolution and with an accuracy and precision better than 5 ms. The availability of such precise timing information, which also includes the identification of the load and the sort of power event, is an essential requirement both for the evaluation of NILM algorithms and techniques, as well as for the training of NILM systems, particularly those based on Machine Learning.
A NILM dataset is a valuable tool in the development of Non-Intrusive Load Monitoring techniques, as it provides a means of evaluation of novel techniques and algorithms, as well as for benchmarking. The figure of merit of a NILM dataset includes characteristics such as the sampling frequency of the voltage, current, or power, the availability of indications (ground-truth) of load events during recording, the variety and representativeness of the loads, and the variety of situations these loads are subject to. Considering such aspects, the proposed LIT-Dataset was designed, populated, evaluated, and made publicly available to support NILM development. Among the distinct features of the LIT-Dataset is the labeling of the load events at sample level resolution and with an accuracy and precision better than 5 ms. The availability of such precise timing information, which also includes the identification of the load and the sort of power event, is an essential requirement both for the evaluation of NILM algorithms and techniques, as well as for the training of NILM systems, particularly those based on Machine Learning.
Record ID
Keywords
electric load simulation, NILM datasets, Non-Intrusive Load Monitoring (NILM), power signature
Subject
Suggested Citation
Renaux DPB, Pottker F, Ancelmo HC, Lazzaretti AE, Lima CRE, Linhares RR, Oroski E, Nolasco LDS, Lima LT, Mulinari BM, Silva JRLD, Omori JS, Santos RBD. A Dataset for Non-Intrusive Load Monitoring: Design and Implementation. (2023). LAPSE:2023.26995
Author Affiliations
Renaux DPB: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Pottker F: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Ancelmo HC: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Lazzaretti AE: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Lima CRE: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Linhares RR: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Oroski E: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Nolasco LDS: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Lima LT: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Mulinari BM: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Silva JRLD: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Omori JS: COPEL-Companhia Paranaense de Energia, José Izidoro Biazetto, 158, Curitiba 82305-100, Brazil
Santos RBD: COPEL-Companhia Paranaense de Energia, José Izidoro Biazetto, 158, Curitiba 82305-100, Brazil [ORCID]
Pottker F: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Ancelmo HC: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Lazzaretti AE: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Lima CRE: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Linhares RR: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Oroski E: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Nolasco LDS: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Lima LT: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Mulinari BM: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Silva JRLD: LIT-Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná-UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil [ORCID]
Omori JS: COPEL-Companhia Paranaense de Energia, José Izidoro Biazetto, 158, Curitiba 82305-100, Brazil
Santos RBD: COPEL-Companhia Paranaense de Energia, José Izidoro Biazetto, 158, Curitiba 82305-100, Brazil [ORCID]
Journal Name
Energies
Volume
13
Issue
20
Article Number
E5371
Year
2020
Publication Date
2020-10-15
ISSN
1996-1073
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PII: en13205371, Publication Type: Journal Article
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LAPSE:2023.26995
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