2020年1月
強化学習によるリニア式波力発電装置の電力量最大化
日本船舶海洋工学会論文集
- ,
- 巻
- 31
- 号
- 0
- 開始ページ
- 229
- 終了ページ
- 238
- 記述言語
- 日本語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.2534/jjasnaoe.31.229
- 出版者・発行元
- 公益社団法人 日本船舶海洋工学会
<p>This paper presents a deep reinforcement learning control method to maximize output energy for a point absorber type wave energy converter (WEC) with a linear generator. Conventional control methods require the dynamic model of the WEC. Modeling errors of the dynamic model, however, make energy absorption smaller and cause incorrect control. The proposed method, which is a model-free control method learns the optimal damping and stiffness coefficients based on experiences. In the proposed control method, damping and stiffness coefficients are able to vary in time-domain depending on the incident waves by deep reinforcement learning. The performance of the proposed control method is investigated through numerical simulation in both regular and irregular waves. Compared with the conventional control method, averaged output power increased, and the power fluctuation decreased without the dynamic model. It is understood that the proposed method is more effective than the conventional control method.</p>
- リンク情報
- ID情報
-
- DOI : 10.2534/jjasnaoe.31.229
- ISSN : 1880-3717
- CiNii Articles ID : 130007905603
- CiNii Books ID : AA12057769