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

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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.

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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.

Item Type:

Conference or Workshop Item (Paper)

RIS ID:

https://nottingham-repository.worktribe.com/output/881816

Keywords:

Estimation technique, Power management, Regulation, Simulation

Schools/Departments:

University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering

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