Control Design of Hybrid Photovoltaic/Fuel Cell for Maximum Power Point Tracking Using Multi Input DC/DC converter Based on Artificial Neural Network

カテゴリ: 部門大会

論文No: 207

グループ名: 【B】平成29年電気学会電力・エネルギー部門大会

発行日: 2017/09/05

タイトル(英語): Control Design of Hybrid Photovoltaic/Fuel Cell for Maximum Power Point Tracking Using Multi Input DC/DC converter Based on Artificial Neural Network

著者名: PAMUJI Feby Agung(熊本大学),宮内 肇(熊本大学)

著者名(英語): PAMUJI Feby Agung|Hajime Miyauchi

キーワード: 最大電力点追従制御|ニューラルネットワーク|太陽光発電|燃料電池|多入力DC/DCコンバータ,Maximum Power Point Tracking,Artificial Neural Network,Photovoltaic,Fuel Cell,Multi Input DC/ DC converter

要約(日本語): In this paper we propose a new control method of hybrid Photovoltaic System (PV) and Fuel Cell System (FC) to get maximum power. ANN controls the multi input DC/ DC converter to shift the PV Voltage to optimum Voltage. The FC helps the PV to fulfill the demand of load, because the PV depends on sun light. From the simulation using Mathlab, we can see that the power of PV and efficiency of FC are increasing by using MPPT controller.

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