Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage

Matthew McCrory; Adele H.  Marshall; Aleksandar Novakovic; Geoffrey Collins

doi:10.1007/978-981-99-3236-8_23

Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage

Matthew McCrory, Adele H. Marshall^*, Aleksandar Novakovic, Geoffrey Collins

^*Corresponding author for this work

School of Mathematics and Physics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Non-intrusive load monitoring (NILM) disaggregates energy consumption data collected from a single measurement point into appliance-level data. This process facilitates energy savings. Most studies treat NILM as a residential task with few considering its application in industry. By chronologically reviewing existing literature, this paper presents a review of the latest research in NILM, focusing on its potential employment within a utility company, Northern Ireland Water. A practical example of NILM is also provided using data collected by a pilot IoT device where the benefits of NILM are exhibited via a cost analysis. Results from the literature review show deep learning models to be the most recent preferred disaggregation approach. Furthermore, the standardization of evaluation metrics is deemed essential to facilitate the comparison of different disaggregation models. Finally, the NILM tool kit is outlined as a useful platform for Northern Ireland Water to practically implement NILM.

Original language	English
Title of host publication	Proceedings of Eighth International Congress on Information and Communication Technology, ICICT 2023
Editors	Xin-She Yang, R. Simon Sherratt, Nilanjan Dey, Amit Joshi
Publisher	Springer
Pages	293–307
Number of pages	11
Volume	4
ISBN (Electronic)	9789819932368
ISBN (Print)	9789819932351
DOIs	https://doi.org/10.1007/978-981-99-3236-8_23
Publication status	Published - 15 Sept 2023
Event	Eighth International Congress on Information and Communication Technology, ICICT 2023 - London Duration: 20 Feb 2023 → 23 Feb 2023

Publication series

Name	Lecture Notes in Networks and Systems
Publisher	Springer
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	Eighth International Congress on Information and Communication Technology, ICICT 2023
City	London
Period	20/02/2023 → 23/02/2023

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Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage
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Accepted author manuscript, 373 KBLicence: Unspecified

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McCrory, M., Marshall, A. H., Novakovic, A., & Collins, G. (2023). Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage. In X.-S. Yang, R. S. Sherratt, N. Dey, & A. Joshi (Eds.), Proceedings of Eighth International Congress on Information and Communication Technology, ICICT 2023 (Vol. 4, pp. 293–307). (Lecture Notes in Networks and Systems). Springer. https://doi.org/10.1007/978-981-99-3236-8_23

McCrory, Matthew ; Marshall, Adele H. ; Novakovic, Aleksandar et al. / Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage. Proceedings of Eighth International Congress on Information and Communication Technology, ICICT 2023. editor / Xin-She Yang ; R. Simon Sherratt ; Nilanjan Dey ; Amit Joshi. Vol. 4 Springer, 2023. pp. 293–307 (Lecture Notes in Networks and Systems).

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title = "Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage",

abstract = "Non-intrusive load monitoring (NILM) disaggregates energy consumption data collected from a single measurement point into appliance-level data. This process facilitates energy savings. Most studies treat NILM as a residential task with few considering its application in industry. By chronologically reviewing existing literature, this paper presents a review of the latest research in NILM, focusing on its potential employment within a utility company, Northern Ireland Water. A practical example of NILM is also provided using data collected by a pilot IoT device where the benefits of NILM are exhibited via a cost analysis. Results from the literature review show deep learning models to be the most recent preferred disaggregation approach. Furthermore, the standardization of evaluation metrics is deemed essential to facilitate the comparison of different disaggregation models. Finally, the NILM tool kit is outlined as a useful platform for Northern Ireland Water to practically implement NILM.",

author = "Matthew McCrory and Marshall, {Adele H.} and Aleksandar Novakovic and Geoffrey Collins",

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McCrory, M, Marshall, AH , Novakovic, A & Collins, G 2023, Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage. in X-S Yang, RS Sherratt, N Dey & A Joshi (eds), Proceedings of Eighth International Congress on Information and Communication Technology, ICICT 2023. vol. 4, Lecture Notes in Networks and Systems, Springer, pp. 293–307, Eighth International Congress on Information and Communication Technology, ICICT 2023, London, 20/02/2023. https://doi.org/10.1007/978-981-99-3236-8_23

Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage. / McCrory, Matthew; Marshall, Adele H. ; Novakovic, Aleksandar et al.
Proceedings of Eighth International Congress on Information and Communication Technology, ICICT 2023. ed. / Xin-She Yang; R. Simon Sherratt; Nilanjan Dey; Amit Joshi. Vol. 4 Springer, 2023. p. 293–307 (Lecture Notes in Networks and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage

AU - McCrory, Matthew

AU - Marshall, Adele H.

AU - Novakovic, Aleksandar

AU - Collins, Geoffrey

PY - 2023/9/15

Y1 - 2023/9/15

N2 - Non-intrusive load monitoring (NILM) disaggregates energy consumption data collected from a single measurement point into appliance-level data. This process facilitates energy savings. Most studies treat NILM as a residential task with few considering its application in industry. By chronologically reviewing existing literature, this paper presents a review of the latest research in NILM, focusing on its potential employment within a utility company, Northern Ireland Water. A practical example of NILM is also provided using data collected by a pilot IoT device where the benefits of NILM are exhibited via a cost analysis. Results from the literature review show deep learning models to be the most recent preferred disaggregation approach. Furthermore, the standardization of evaluation metrics is deemed essential to facilitate the comparison of different disaggregation models. Finally, the NILM tool kit is outlined as a useful platform for Northern Ireland Water to practically implement NILM.

AB - Non-intrusive load monitoring (NILM) disaggregates energy consumption data collected from a single measurement point into appliance-level data. This process facilitates energy savings. Most studies treat NILM as a residential task with few considering its application in industry. By chronologically reviewing existing literature, this paper presents a review of the latest research in NILM, focusing on its potential employment within a utility company, Northern Ireland Water. A practical example of NILM is also provided using data collected by a pilot IoT device where the benefits of NILM are exhibited via a cost analysis. Results from the literature review show deep learning models to be the most recent preferred disaggregation approach. Furthermore, the standardization of evaluation metrics is deemed essential to facilitate the comparison of different disaggregation models. Finally, the NILM tool kit is outlined as a useful platform for Northern Ireland Water to practically implement NILM.

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McCrory M, Marshall AH , Novakovic A, Collins G. Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage. In Yang XS, Sherratt RS, Dey N, Joshi A, editors, Proceedings of Eighth International Congress on Information and Communication Technology, ICICT 2023. Vol. 4. Springer. 2023. p. 293–307. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-99-3236-8_23

Reviewing non-intrusive load monitoring using a pilot study of an IoT device to disaggregate energy usage

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