Chronological categorization and decomposition of customer loads
The majority of distribution utilities do not have accurate information on the constituents of their loads. This information is very useful in managing and planning the network, adequately and economically. Customer loads are normally categorized in three main sectors: 1) residential; 2) industrial;...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
IEEE Power Engineering Society
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/40292 |
| _version_ | 1848755829734375424 |
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| author | Nourbakhsh, G. Eden, G. McVeigh, D. Ghosh, Arindam |
| author_facet | Nourbakhsh, G. Eden, G. McVeigh, D. Ghosh, Arindam |
| author_sort | Nourbakhsh, G. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The majority of distribution utilities do not have accurate information on the constituents of their loads. This information is very useful in managing and planning the network, adequately and economically. Customer loads are normally categorized in three main sectors: 1) residential; 2) industrial; and3) commercial. In this paper, penalized least-squares regression and Euclidean distance methods are developed for this application to identify and quantify the makeup of a feeder load with unknown sectors/subsectors. This process is done on a monthly basis to account for seasonal and other load changes. The error between the actual and estimated load profiles are used as a benchmark of accuracy. This approach has shown to be accurate in identifying customer types in unknown load profiles, and is used in cross-validation of the results and initial assumptions. |
| first_indexed | 2025-11-14T09:02:32Z |
| format | Journal Article |
| id | curtin-20.500.11937-40292 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:02:32Z |
| publishDate | 2012 |
| publisher | IEEE Power Engineering Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-402922017-02-28T01:37:06Z Chronological categorization and decomposition of customer loads Nourbakhsh, G. Eden, G. McVeigh, D. Ghosh, Arindam The majority of distribution utilities do not have accurate information on the constituents of their loads. This information is very useful in managing and planning the network, adequately and economically. Customer loads are normally categorized in three main sectors: 1) residential; 2) industrial; and3) commercial. In this paper, penalized least-squares regression and Euclidean distance methods are developed for this application to identify and quantify the makeup of a feeder load with unknown sectors/subsectors. This process is done on a monthly basis to account for seasonal and other load changes. The error between the actual and estimated load profiles are used as a benchmark of accuracy. This approach has shown to be accurate in identifying customer types in unknown load profiles, and is used in cross-validation of the results and initial assumptions. 2012 Journal Article http://hdl.handle.net/20.500.11937/40292 IEEE Power Engineering Society restricted |
| spellingShingle | Nourbakhsh, G. Eden, G. McVeigh, D. Ghosh, Arindam Chronological categorization and decomposition of customer loads |
| title | Chronological categorization and decomposition of customer loads |
| title_full | Chronological categorization and decomposition of customer loads |
| title_fullStr | Chronological categorization and decomposition of customer loads |
| title_full_unstemmed | Chronological categorization and decomposition of customer loads |
| title_short | Chronological categorization and decomposition of customer loads |
| title_sort | chronological categorization and decomposition of customer loads |
| url | http://hdl.handle.net/20.500.11937/40292 |