Analysis of household electricity consumption behaviours: impact of domestic electricity generation

Adoption of renewable electricity generation technology such as photovoltaic (PV) systems is at early majority stage in most countries. Depending on solar capacity, applied feed-in tariff, and other factors, households exhibit different electricity consumption behaviours known as demand side managem...

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Main Authors: Motlagh, Omd, Paevere, Phillip, Tang, Sai Hong, Grozev, George
Format: Article
Language:English
Published: Elsevier 2015
Online Access:http://psasir.upm.edu.my/id/eprint/43754/1/sad.pdf
http://psasir.upm.edu.my/id/eprint/43754/
http://www.elsevier.com/locate/amc
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Institution: Universiti Putra Malaysia
Language: English
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spelling my.upm.eprints.437542016-09-20T08:29:04Z http://psasir.upm.edu.my/id/eprint/43754/ Analysis of household electricity consumption behaviours: impact of domestic electricity generation Motlagh, Omd Paevere, Phillip Tang, Sai Hong Grozev, George Adoption of renewable electricity generation technology such as photovoltaic (PV) systems is at early majority stage in most countries. Depending on solar capacity, applied feed-in tariff, and other factors, households exhibit different electricity consumption behaviours known as demand side management. This article presents three univariate methods to infer deliberative behavioural patterns at households with solar electricity technology. Strategies include qualitative principal component analysis (PCA), unsupervised Hebbian-based clustering, and clustering using a semi-supervised self-organizing map (SOM). The models are individually examined on 300 sample households with rooftop PV panels under gross metering. According to the experiments, the dominant behaviours are often general among most households, and therefore reveal themselves on first and second principal components. However, on the third and forth component the specific behaviours related to load-shifting and self-consumption, are observed. The Hebbian classifier differentiates between at least eight behaviours some of which indicating deliberative behaviours. More effectively, the SOM classifier allows for clear detection of self-consumption behaviour attributed to domestic electricity generation. The experiments, results, discussions, and recommendations for future work are inclusive. Elsevier 2015-11-01 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/43754/1/sad.pdf Motlagh, Omd and Paevere, Phillip and Tang, Sai Hong and Grozev, George (2015) Analysis of household electricity consumption behaviours: impact of domestic electricity generation. Applied Mathematics and Computation, 270. pp. 165-178. ISSN 0096-3003 http://www.elsevier.com/locate/amc 10.1016/j.amc.2015.08.029
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Adoption of renewable electricity generation technology such as photovoltaic (PV) systems is at early majority stage in most countries. Depending on solar capacity, applied feed-in tariff, and other factors, households exhibit different electricity consumption behaviours known as demand side management. This article presents three univariate methods to infer deliberative behavioural patterns at households with solar electricity technology. Strategies include qualitative principal component analysis (PCA), unsupervised Hebbian-based clustering, and clustering using a semi-supervised self-organizing map (SOM). The models are individually examined on 300 sample households with rooftop PV panels under gross metering. According to the experiments, the dominant behaviours are often general among most households, and therefore reveal themselves on first and second principal components. However, on the third and forth component the specific behaviours related to load-shifting and self-consumption, are observed. The Hebbian classifier differentiates between at least eight behaviours some of which indicating deliberative behaviours. More effectively, the SOM classifier allows for clear detection of self-consumption behaviour attributed to domestic electricity generation. The experiments, results, discussions, and recommendations for future work are inclusive.
format Article
author Motlagh, Omd
Paevere, Phillip
Tang, Sai Hong
Grozev, George
spellingShingle Motlagh, Omd
Paevere, Phillip
Tang, Sai Hong
Grozev, George
Analysis of household electricity consumption behaviours: impact of domestic electricity generation
author_facet Motlagh, Omd
Paevere, Phillip
Tang, Sai Hong
Grozev, George
author_sort Motlagh, Omd
title Analysis of household electricity consumption behaviours: impact of domestic electricity generation
title_short Analysis of household electricity consumption behaviours: impact of domestic electricity generation
title_full Analysis of household electricity consumption behaviours: impact of domestic electricity generation
title_fullStr Analysis of household electricity consumption behaviours: impact of domestic electricity generation
title_full_unstemmed Analysis of household electricity consumption behaviours: impact of domestic electricity generation
title_sort analysis of household electricity consumption behaviours: impact of domestic electricity generation
publisher Elsevier
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/43754/1/sad.pdf
http://psasir.upm.edu.my/id/eprint/43754/
http://www.elsevier.com/locate/amc
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