Mitigation of High Frequency Components using ANN

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Bol In this study, an ANN was used to predict the high-frequency components of the system and to develop a control strategy to mitigate their effects. The results of the study showed that the ANN was able to accurately predict the high-frequency components of the system and that the control strategy was able to effectively mitigate their effects. This study demonstrates the potential of ANNs for mitigating the high-frequency components in a modern distribution system. This work presents a novel approach to mitigating high-frequency components in a modern distribution system using an Artificial Neural Network (ANN). The proposed method utilizes the capability of an ANN to learn the complex relationship between system parameters and high-frequency voltage harmonics. The trained ANN model is then used to predict the high-frequency components and generate control signals to mitigate them.

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In this study, an ANN was used to predict the high-frequency components of the system and to develop a control strategy to mitigate their effects. The results of the study showed that the ANN was able to accurately predict the high-frequency components of the system and that the control strategy was able to effectively mitigate their effects. This study demonstrates the potential of ANNs for mitigating the high-frequency components in a modern distribution system. This work presents a novel approach to mitigating high-frequency components in a modern distribution system using an Artificial Neural Network (ANN). The proposed method utilizes the capability of an ANN to learn the complex relationship between system parameters and high-frequency voltage harmonics. The trained ANN model is then used to predict the high-frequency components and generate control signals to mitigate them.

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Pages: 80, Paperback, LAP Lambert Academic Publishing


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Merk LAP LAMBERT Academic Publishing
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  • 9786208415204
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