Projects per year
Abstract
This work addresses with sensitivity and uncertainty of the energy conversion of an oscillation-body wave energy converter with an artificial neural-network-based controller. The smart controller applies the model predictive control strategy to implement real-time latching control to the wave energy converter. Since the control inputs are future wave forces, an artificial neural network is developed and trained by the machine learning algorithm to predict the short-term wave forces based on the real-time measurement of wave elevation. The sensitivity of wave energy conversion with respect to wave frequency and receding horizon length are investigated. Uncertainties of the neural network that lead to the prediction deviation are identified and quantified, and their influences on the energy conversion are examined. The control command is derived inappropriately in the presence of prediction deviation leading to the reduction of energy absorption. Moreover, it is the phase deviation that reduces the energy absorption.
Original language | English |
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Pages (from-to) | 282-293 |
Number of pages | 12 |
Journal | Ocean Engineering |
Volume | 183 |
Early online date | 16 May 2019 |
DOIs | |
Publication status | Published - 1 Jul 2019 |
Keywords
- artificial intelligence
- artificial neural network
- machine learning
- model predictive control
- wave energy
- wave force prediction
Fingerprint
Dive into the research topics of 'On the sensitivity and uncertainty of wave energy conversion with an artificial neural-network-based controller'. Together they form a unique fingerprint.Projects
- 1 Finished
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ETP PECRE: Real-time spectral control of wave energy converter with consideration of wave force prediction
Li, L.
12/07/18 → 12/09/18
Project: Research
Research output
- 31 Citations
- 2 Article
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Wave force prediction effect on the energy absorption of a wave energy converter with real-time control
Li, L., Yuan, Z., Gao, Y. & Zhang, X., 30 Apr 2019, In: IEEE Transactions on Sustainable Energy. 10, 2, p. 615-624 10 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile23 Citations (Scopus)96 Downloads (Pure) -
Maximization of energy absorption for a wave energy converter using the deep machine learning
Li, L., Yuan, Z. & Gao, Y., 15 Dec 2018, In: Energy. 165, Part A, p. 340-349 10 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile48 Citations (Scopus)93 Downloads (Pure)
Activities
- 1 Visiting an external academic institution
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Norwegian University of Science and Technology (NTNU)
Liang Li (Visiting researcher)
1 Jul 2018 → 1 Sep 2018Activity: Visiting an external institution types › Visiting an external academic institution