Statistical appraisal of economic design strategies of LV distribution networks
This paper presents a statistical approach for assessing general LV distribution network design strategies based on a large set of realistic test networks and optimal economic circuit design. The test networks are generated using a fractal-based algorithm that allows creation of generic networks wit...
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Elsevier B.V.
2011
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my.utem.eprints.38632023-05-29T14:56:23Z http://eprints.utem.edu.my/id/eprint/3863/ Statistical appraisal of economic design strategies of LV distribution networks Gan, Chin Kim Pierluigi, Mancarella Pudjianto, Danny Strbac, Goran TK Electrical engineering. Electronics Nuclear engineering This paper presents a statistical approach for assessing general LV distribution network design strategies based on a large set of realistic test networks and optimal economic circuit design. The test networks are generated using a fractal-based algorithm that allows creation of generic networks with various topological features (e.g., typical of rural/urban/mixed areas) and characterised by different numbers of substations, numbers of customers, load densities, and so forth. In comparison to standards derived from a traditional approach, that is, case studies on a small number of specific real or test networks, the proposed approach facilitates the derivation of more robust conclusions on optimal network design policies and can thus be used as a valuable tool for decision support. The methodology is exemplified through numerical applications for both urban and rural areas. Elsevier B.V. 2011-07 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/3863/1/1-s2.0-S0378779611000368-main.pdf Gan, Chin Kim and Pierluigi, Mancarella and Pudjianto, Danny and Strbac, Goran (2011) Statistical appraisal of economic design strategies of LV distribution networks. Electric Power Systems Research, 81 (7). pp. 1363-1372. ISSN 0378-7796 https://www.sciencedirect.com/science/article/pii/S0378779611000368 10.1016/j.epsr.2011.02.001 |
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TK Electrical engineering. Electronics Nuclear engineering Gan, Chin Kim Pierluigi, Mancarella Pudjianto, Danny Strbac, Goran Statistical appraisal of economic design strategies of LV distribution networks |
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This paper presents a statistical approach for assessing general LV distribution network design strategies based on a large set of realistic test networks and optimal economic circuit design. The test networks are generated using a fractal-based algorithm that allows creation of generic networks with various topological features (e.g., typical of rural/urban/mixed areas) and characterised by different numbers of substations, numbers of customers, load densities, and so forth. In comparison to standards derived from a traditional approach, that is, case studies on a small number of specific real or test networks, the proposed approach facilitates the derivation of more robust conclusions on optimal network design policies and can thus be used as a valuable tool for decision support. The methodology is exemplified through numerical applications for both urban and rural areas. |
format |
Article |
author |
Gan, Chin Kim Pierluigi, Mancarella Pudjianto, Danny Strbac, Goran |
author_facet |
Gan, Chin Kim Pierluigi, Mancarella Pudjianto, Danny Strbac, Goran |
author_sort |
Gan, Chin Kim |
title |
Statistical appraisal of economic design strategies of LV distribution networks |
title_short |
Statistical appraisal of economic design strategies of LV distribution networks |
title_full |
Statistical appraisal of economic design strategies of LV distribution networks |
title_fullStr |
Statistical appraisal of economic design strategies of LV distribution networks |
title_full_unstemmed |
Statistical appraisal of economic design strategies of LV distribution networks |
title_sort |
statistical appraisal of economic design strategies of lv distribution networks |
publisher |
Elsevier B.V. |
publishDate |
2011 |
url |
http://eprints.utem.edu.my/id/eprint/3863/1/1-s2.0-S0378779611000368-main.pdf http://eprints.utem.edu.my/id/eprint/3863/ https://www.sciencedirect.com/science/article/pii/S0378779611000368 |
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13.18916 |