Design and development of an Artificial Neural Network-based Maximum Power Point Tracker (ANN_MPPT) for the residential solar photovoltaic
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- 鳥飼 凌太郎
- 九州大学大学院総合理工学府
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- Farzaneh Hooman
- 九州大学大学院総合理工学府 九州大学グリーンテクノロジー研究教育センター
抄録
In recent years, solar power generation systems have been evolving from the perspective of mitigating global warming. The Maximum Power Point Tracking (MPPT) method is a notable method garnering attention. In this study, two MPPT methods were compared using MATLAB/Simulink. One method employed the perturb and observe technique, while the other utilized Artificial Neural Networks (ANN). The comparison results revealed that the power generation system using the ANN-based approach generated more electricity than the perturb and observe method.
収録刊行物
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- Proceedings of International Exchange and Innovation Conference on Engineering & Sciences (IEICES)
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Proceedings of International Exchange and Innovation Conference on Engineering & Sciences (IEICES) 9 321-326, 2023-10-19
九州大学大学院総合理工学府
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詳細情報 詳細情報について
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- CRID
- 1390861305866501760
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- DOI
- 10.5109/7157996
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- HANDLE
- 2324/7157996
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- ISSN
- 24341436
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- IRDB
- Crossref
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- 抄録ライセンスフラグ
- 使用可