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 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