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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2015
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| Online Access: | http://psasir.upm.edu.my/id/eprint/43754/ http://psasir.upm.edu.my/id/eprint/43754/1/sad.pdf |
| _version_ | 1848850313700704256 |
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| author | Motlagh, Omd Paevere, Phillip Tang, Sai Hong Grozev, George |
| author_facet | Motlagh, Omd Paevere, Phillip Tang, Sai Hong Grozev, George |
| author_sort | Motlagh, Omd |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T10:04:18Z |
| format | Article |
| id | upm-43754 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:04:18Z |
| publishDate | 2015 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| spellingShingle | Motlagh, Omd Paevere, Phillip Tang, Sai Hong Grozev, George Analysis of household electricity consumption behaviours: impact of domestic electricity generation |
| title | 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_short | Analysis of household electricity consumption behaviours: impact of domestic electricity generation |
| title_sort | analysis of household electricity consumption behaviours: impact of domestic electricity generation |
| url | http://psasir.upm.edu.my/id/eprint/43754/ http://psasir.upm.edu.my/id/eprint/43754/ http://psasir.upm.edu.my/id/eprint/43754/ http://psasir.upm.edu.my/id/eprint/43754/1/sad.pdf |