Current Compensation Method in a Distribution System Based on a Four-Leg Inverter under Unbalanced Load Conditions Using an Artificial Neural Network

Tae-Gyu Kim, Chang-Gyun An, Junsin Yi and Chung-Yuen Won ()
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Tae-Gyu Kim: Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
Chang-Gyun An: Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
Junsin Yi: Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
Chung-Yuen Won: Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea

Energies, 2024, vol. 17, issue 6, 1-29

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.

Keywords: unbalanced current compensation; artificial neural network; four-leg inverter; grid-connected (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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