A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities
The continuing trend toward heavier load and high penetration of Distribution Generation (DG) units in low voltage rural distribution feeders requires power electronic-based solution alternatives for voltage regulation purposes. The design of power electronics in terms of size and cost used for feed...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2017
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| Online Access: | https://eprints.nottingham.ac.uk/44836/ |
| _version_ | 1848797009578819584 |
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| author | Ganjavi, Amin Christopher, Edward Johnson, Christopher Mark Clare, Jon C. |
| author_facet | Ganjavi, Amin Christopher, Edward Johnson, Christopher Mark Clare, Jon C. |
| author_sort | Ganjavi, Amin |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The continuing trend toward heavier load and high penetration of Distribution Generation (DG) units in low voltage rural distribution feeders requires power electronic-based solution alternatives for voltage regulation purposes. The design of power electronics in terms of size and cost used for feeder voltage regulation is proportional to their KVA ratings. An iterative optimisation algorithm known as Expectation Maximization (EM) is used to identify a powerful probability model known as Gaussian Mixture Model (GMM). This leads to find an optimum KVA rating based on probabilities. |
| first_indexed | 2025-11-14T19:57:04Z |
| format | Conference or Workshop Item |
| id | nottingham-44836 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:57:04Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-448362020-05-04T19:05:33Z https://eprints.nottingham.ac.uk/44836/ A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities Ganjavi, Amin Christopher, Edward Johnson, Christopher Mark Clare, Jon C. The continuing trend toward heavier load and high penetration of Distribution Generation (DG) units in low voltage rural distribution feeders requires power electronic-based solution alternatives for voltage regulation purposes. The design of power electronics in terms of size and cost used for feeder voltage regulation is proportional to their KVA ratings. An iterative optimisation algorithm known as Expectation Maximization (EM) is used to identify a powerful probability model known as Gaussian Mixture Model (GMM). This leads to find an optimum KVA rating based on probabilities. 2017-09-11 Conference or Workshop Item PeerReviewed Ganjavi, Amin, Christopher, Edward, Johnson, Christopher Mark and Clare, Jon C. (2017) A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities. In: EPE 2017 ECCE Europe, 11-14 Sept 2017, Warsaw, Poland. Estimation technique Power management Regulation Simulation |
| spellingShingle | Estimation technique Power management Regulation Simulation Ganjavi, Amin Christopher, Edward Johnson, Christopher Mark Clare, Jon C. A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities |
| title | A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities |
| title_full | A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities |
| title_fullStr | A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities |
| title_full_unstemmed | A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities |
| title_short | A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities |
| title_sort | new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities |
| topic | Estimation technique Power management Regulation Simulation |
| url | https://eprints.nottingham.ac.uk/44836/ |