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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.

Authors

Amin Ganjavi Amin.Ganjavi@nottingham.ac.uk

Edward Christopher edward.christopher@nottingham.ac.uk

Christopher Mark Johnson mark.johnson@nottingham.ac.uk

Jon C. Clare jon.clare@nottingham.ac.uk



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.

Publication Date Sep 11, 2017
Peer Reviewed Peer Reviewed
APA6 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
Keywords Estimation technique, Power management, Regulation, Simulation
Related Public URLs http://www.epe2017.com/
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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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 (792 Kb)
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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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