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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.

A new analysis for finding the optimum power rating of low voltage distribution power electronics based on statistics and probabilities Thumbnail


Authors

Amin Ganjavi

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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