Affiliation:
1. Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
Abstract
This study proposes an unbalanced current compensation method based on a four-leg inverter using an artificial neural network (ANN) under unbalanced load conditions. Distribution systems exhibit rapid load variations, and conventional filter-based control methods suffer from the drawback of requiring an extended time period to reach a steady state. To address this problem, an ANN is applied to calculate the unbalanced current reference and enhance dynamic performance. Additionally, because of the periodic incorrect output inherent in the ANN, applying it to a proportional–integral controller would result in an error being directly reflected in the current reference. In the aforementioned problem, an ANN is applied to the dq0 coordinate system current controller to compensate for the periodic incorrect output in the current reference calculation. The proposed ANN-based unbalanced current compensation method is validated through PSIM simulations and experiments.
Funder
Korea Institute of Energy Technology Evaluation and Planning
Ministry of Trade, Industry, and Energy (MOTIE) of the Republic of Korea
BK21 FOUR Project
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