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Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling. / Wu, Yueqi; Sheng, Wanan; Taylor, C. James et al.
The 33rd International Ocean and Polar Engineering Conference, Ottawa, Canada, June 2023: ISOPE 2023. ISOPE, 2023. p. 657-662 ISOPE-I-23-095.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Wu, Y, Sheng, W, Taylor, CJ, Aggidis, G & Ma, X 2023, Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling. in The 33rd International Ocean and Polar Engineering Conference, Ottawa, Canada, June 2023: ISOPE 2023., ISOPE-I-23-095, ISOPE, pp. 657-662. <https://onepetro.org/ISOPEIOPEC/proceedings-abstract/ISOPE23/All-ISOPE23/524528>

APA

Wu, Y., Sheng, W., Taylor, C. J., Aggidis, G., & Ma, X. (2023). Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling. In The 33rd International Ocean and Polar Engineering Conference, Ottawa, Canada, June 2023: ISOPE 2023 (pp. 657-662). Article ISOPE-I-23-095 ISOPE. https://onepetro.org/ISOPEIOPEC/proceedings-abstract/ISOPE23/All-ISOPE23/524528

Vancouver

Wu Y, Sheng W, Taylor CJ, Aggidis G, Ma X. Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling. In The 33rd International Ocean and Polar Engineering Conference, Ottawa, Canada, June 2023: ISOPE 2023. ISOPE. 2023. p. 657-662. ISOPE-I-23-095

Author

Wu, Yueqi ; Sheng, Wanan ; Taylor, C. James et al. / Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling. The 33rd International Ocean and Polar Engineering Conference, Ottawa, Canada, June 2023: ISOPE 2023. ISOPE, 2023. pp. 657-662

Bibtex

@inproceedings{55d09ed5008f4f139587d54cb781070a,
title = "Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling",
abstract = "Wave energy shows potential to provide electricity in a renewable manner. The TALOS WEC (Wave Energy Converter) is a unique design with six PTO (Power Take-Off) elements to provide six Degrees of Freedom (DOFs), which is potentially able to harvest energy more efficiently than traditional single-DOF devices. As a step towards its optimisation and control, a power prediction model is developed, using the wave elevation and motions of the WEC to predict the power output of each PTO. The results show that using LSTM (Long-Short Term Memory) has a higher prediction accuracy than the other approaches considered.",
keywords = "TALOS, WEC, Power prediction, Machine learning, LSTM",
author = "Yueqi Wu and Wanan Sheng and Taylor, {C. James} and George Aggidis and Xiandong Ma",
year = "2023",
month = jun,
day = "19",
language = "English",
isbn = " 9781880653807",
pages = "657--662",
booktitle = "The 33rd International Ocean and Polar Engineering Conference, Ottawa, Canada, June 2023",
publisher = "ISOPE",

}

RIS

TY - GEN

T1 - Long-Short Term Memory Based TALOS Wave Energy Converter Power Output Prediction with Numerical Modelling

AU - Wu, Yueqi

AU - Sheng, Wanan

AU - Taylor, C. James

AU - Aggidis, George

AU - Ma, Xiandong

PY - 2023/6/19

Y1 - 2023/6/19

N2 - Wave energy shows potential to provide electricity in a renewable manner. The TALOS WEC (Wave Energy Converter) is a unique design with six PTO (Power Take-Off) elements to provide six Degrees of Freedom (DOFs), which is potentially able to harvest energy more efficiently than traditional single-DOF devices. As a step towards its optimisation and control, a power prediction model is developed, using the wave elevation and motions of the WEC to predict the power output of each PTO. The results show that using LSTM (Long-Short Term Memory) has a higher prediction accuracy than the other approaches considered.

AB - Wave energy shows potential to provide electricity in a renewable manner. The TALOS WEC (Wave Energy Converter) is a unique design with six PTO (Power Take-Off) elements to provide six Degrees of Freedom (DOFs), which is potentially able to harvest energy more efficiently than traditional single-DOF devices. As a step towards its optimisation and control, a power prediction model is developed, using the wave elevation and motions of the WEC to predict the power output of each PTO. The results show that using LSTM (Long-Short Term Memory) has a higher prediction accuracy than the other approaches considered.

KW - TALOS

KW - WEC

KW - Power prediction

KW - Machine learning

KW - LSTM

M3 - Conference contribution/Paper

SN - 9781880653807

SP - 657

EP - 662

BT - The 33rd International Ocean and Polar Engineering Conference, Ottawa, Canada, June 2023

PB - ISOPE

ER -