Deep Learning for Wave Energy Converter Modeling Using Long Short-Term Memory
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Reikard, Gordon & Robertson, Bryson & Bidlot, Jean-Raymond, 2015. "Combining wave energy with wind and solar: Short-term forecasting," Renewable Energy, Elsevier, vol. 81(C), pages 442-456.
- Antonio Manuel Gómez-Orellana & Juan Carlos Fernández & Manuel Dorado-Moreno & Pedro Antonio Gutiérrez & César Hervás-Martínez, 2021. "Building Suitable Datasets for Soft Computing and Machine Learning Techniques from Meteorological Data Integration: A Case Study for Predicting Significant Wave Height and Energy Flux," Energies, MDPI, vol. 14(2), pages 1-33, January.
- Gomes, R.P.F. & Henriques, J.C.C. & Gato, L.M.C. & Falcão, A.F.O., 2012. "Hydrodynamic optimization of an axisymmetric floating oscillating water column for wave energy conversion," Renewable Energy, Elsevier, vol. 44(C), pages 328-339.
- Giorgi, Giuseppe & Gomes, Rui P.F. & Henriques, João C.C. & Gato, Luís M.C. & Bracco, Giovanni & Mattiazzo, Giuliana, 2020. "Detecting parametric resonance in a floating oscillating water column device for wave energy conversion: Numerical simulations and validation with physical model tests," Applied Energy, Elsevier, vol. 276(C).
- Tunde Aderinto & Hua Li, 2018. "Ocean Wave Energy Converters: Status and Challenges," Energies, MDPI, vol. 11(5), pages 1-26, May.
- Sinsel, Simon R. & Riemke, Rhea L. & Hoffmann, Volker H., 2020. "Challenges and solution technologies for the integration of variable renewable energy sources—a review," Renewable Energy, Elsevier, vol. 145(C), pages 2271-2285.
- Chenhua Ni & Xiandong Ma, 2018. "Prediction of Wave Power Generation Using a Convolutional Neural Network with Multiple Inputs," Energies, MDPI, vol. 11(8), pages 1-18, August.
- Erick López & Carlos Valle & Héctor Allende & Esteban Gil & Henrik Madsen, 2018. "Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory," Energies, MDPI, vol. 11(3), pages 1-22, February.
- Li, L. & Gao, Y. & Ning, D.Z. & Yuan, Z.M., 2021. "Development of a constraint non-causal wave energy control algorithm based on artificial intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Chengcheng Gu & Hua Li, 2022. "Review on Deep Learning Research and Applications in Wind and Wave Energy," Energies, MDPI, vol. 15(4), pages 1-19, February.
- Panyu Tang & Mahdi Aghaabbasi & Mujahid Ali & Amin Jan & Abdeliazim Mustafa Mohamed & Abdullah Mohamed, 2022. "How Sustainable Is People’s Travel to Reach Public Transit Stations to Go to Work? A Machine Learning Approach to Reveal Complex Relationships," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
- Fatemehsadat Mirshafiee & Emad Shahbazi & Mohadeseh Safi & Rituraj Rituraj, 2023. "Predicting Power and Hydrogen Generation of a Renewable Energy Converter Utilizing Data-Driven Methods: A Sustainable Smart Grid Case Study," Energies, MDPI, vol. 16(1), pages 1-20, January.
- Jialin Liu & Chen Gong & Suhua Chen & Nanrun Zhou, 2023. "Multi-Step-Ahead Wind Speed Forecast Method Based on Outlier Correction, Optimized Decomposition, and DLinear Model," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Hall, Carrie & Sheng, Wanan & Wu, Yueqi & Aggidis, George, 2024. "The impact of model predictive control structures and constraints on a wave energy converter with hydraulic power take off system," Renewable Energy, Elsevier, vol. 224(C).
- Gradowski, M. & Gomes, R.P.F. & Alves, M., 2020. "Hydrodynamic optimisation of an axisymmetric floating Oscillating Water Column type wave energy converter with an enlarged inner tube," Renewable Energy, Elsevier, vol. 162(C), pages 1519-1532.
- Gomes, Rui P.F. & Gato, Luís M.C. & Henriques, João C.C. & Portillo, Juan C.C. & Howey, Ben D. & Collins, Keri M. & Hann, Martyn R. & Greaves, Deborah M., 2020. "Compact floating wave energy converters arrays: Mooring loads and survivability through scale physical modelling," Applied Energy, Elsevier, vol. 280(C).
- Oikonomou, Charikleia L.G. & Gomes, Rui P.F. & Gato, Luís M.C., 2021. "Unveiling the potential of using a spar-buoy oscillating-water-column wave energy converter for low-power stand-alone applications," Applied Energy, Elsevier, vol. 292(C).
- Erfan Amini & Rojin Asadi & Danial Golbaz & Mahdieh Nasiri & Seyed Taghi Omid Naeeni & Meysam Majidi Nezhad & Giuseppe Piras & Mehdi Neshat, 2021. "Comparative Study of Oscillating Surge Wave Energy Converter Performance: A Case Study for Southern Coasts of the Caspian Sea," Sustainability, MDPI, vol. 13(19), pages 1-21, October.
- Zhang, Yongxing & Zhao, Yongjie & Sun, Wei & Li, Jiaxuan, 2021. "Ocean wave energy converters: Technical principle, device realization, and performance evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
- Zapata, Sebastian & Castaneda, Monica & Aristizabal, Andres J. & Dyner, Isaac, 2022. "Renewables for supporting supply adequacy in Colombia," Energy, Elsevier, vol. 239(PC).
- Henriques, J.C.C. & Gato, L.M.C. & Falcão, A.F.O. & Robles, E. & Faÿ, F.-X., 2016. "Latching control of a floating oscillating-water-column wave energy converter," Renewable Energy, Elsevier, vol. 90(C), pages 229-241.
- Wang, Mingtao & Zhang, Juan & Liu, Huanwei, 2022. "Thermodynamic analysis and optimization of two low-grade energy driven transcritical CO2 combined cooling, heating and power systems," Energy, Elsevier, vol. 249(C).
- Mehdi Neshat & Nataliia Y. Sergiienko & Erfan Amini & Meysam Majidi Nezhad & Davide Astiaso Garcia & Bradley Alexander & Markus Wagner, 2020. "A New Bi-Level Optimisation Framework for Optimising a Multi-Mode Wave Energy Converter Design: A Case Study for the Marettimo Island, Mediterranean Sea," Energies, MDPI, vol. 13(20), pages 1-23, October.
- Tunde Aderinto & Hua Li, 2020. "Effect of Spatial and Temporal Resolution Data on Design and Power Capture of a Heaving Point Absorber," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
- Bruno Cárdenas & Lawrie Swinfen-Styles & James Rouse & Seamus D. Garvey, 2021. "Short-, Medium-, and Long-Duration Energy Storage in a 100% Renewable Electricity Grid: A UK Case Study," Energies, MDPI, vol. 14(24), pages 1-28, December.
- Licheri, Fabio & Ghisu, Tiziano & Cambuli, Francesco & Puddu, Pierpaolo, 2022. "Detailed investigation of the local flow-field in a Wells turbine coupled to an OWC simulator," Renewable Energy, Elsevier, vol. 197(C), pages 583-593.
- Ivan S. Maksymov, 2023. "Analogue and Physical Reservoir Computing Using Water Waves: Applications in Power Engineering and Beyond," Energies, MDPI, vol. 16(14), pages 1-26, July.
- Wang, Mangkuan & Shang, Jianzhong & Luo, Zirong & Lu, Zhongyue & Yao, Ganzhou, 2023. "Theoretical and numerical studies on improving absorption power of multi-body wave energy convert device with nonlinear bistable structure," Energy, Elsevier, vol. 282(C).
- Julien Walzberg & Annika Eberle, 2023. "Modeling Systems’ Disruption and Social Acceptance—A Proof-of-Concept Leveraging Reinforcement Learning," Sustainability, MDPI, vol. 15(13), pages 1-13, June.
- Shah Rukh Abbas & Syed Ali Abbas Kazmi & Muhammad Naqvi & Adeel Javed & Salman Raza Naqvi & Kafait Ullah & Tauseef-ur-Rehman Khan & Dong Ryeol Shin, 2020. "Impact Analysis of Large-Scale Wind Farms Integration in Weak Transmission Grid from Technical Perspectives," Energies, MDPI, vol. 13(20), pages 1-32, October.
- Abadie, Luis Mª & Chamorro, José M., 2023. "Investment in wind-based hydrogen production under economic and physical uncertainties," Applied Energy, Elsevier, vol. 337(C).
- Yinhe Bu & Xingping Zhang, 2021. "On the Way to Integrate Increasing Shares of Variable Renewables in China: Experience from Flexibility Modification and Deep Peak Regulation Ancillary Service Market Based on MILP-UC Programming," Sustainability, MDPI, vol. 13(5), pages 1-22, February.
- Chenglong Guo & Wanan Sheng & Dakshina G. De Silva & George Aggidis, 2023. "A Review of the Levelized Cost of Wave Energy Based on a Techno-Economic Model," Energies, MDPI, vol. 16(5), pages 1-30, February.
More about this item
Keywords
Searaser; renewable energy; machine learning; long short term memory; deep neural network; deep learning; recurrent neural network; data science; big data; internet of things (IoT);All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:8:p:871-:d:536566. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.