Amin Ganjavi
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.
Authors
Edward Christopher
MARK JOHNSON MARK.JOHNSON@NOTTINGHAM.AC.UK
Professor of Advanced Power Conversion
Jon C. Clare
Abstract
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.
Citation
Ganjavi, A., Christopher, E., Johnson, C. M., & Clare, J. C. (2017). A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities.
Conference Name | EPE 2017 ECCE Europe |
---|---|
End Date | Sep 14, 2017 |
Acceptance Date | Mar 1, 2017 |
Publication Date | Sep 11, 2017 |
Deposit Date | Aug 23, 2017 |
Publicly Available Date | Sep 11, 2017 |
Peer Reviewed | Peer Reviewed |
Keywords | Estimation technique, Power management, Regulation, Simulation |
Public URL | https://nottingham-repository.worktribe.com/output/881816 |
Related Public URLs | http://www.epe2017.com/ |
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A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities.pdf
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