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Reinforcement Learning–Based Multi-Objective Optimization and Adaptive Control of Grid-Connected Tidal Energy Systems for Sustainable Coastal Power Generation under Stochastic Marine Conditions
Authors
1 Professor, Utilities and Sustainable Engineering, the University of Trinidad & Tobago UTT
Article Information
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- Year 2026 · Volume 3 · Issue 2
- Published Online
- May-August 2026
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- 01-16
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- Original Article
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References
1. Y. Li, J. Liu, and K. Yang, “Global assessment of tidal stream energy potential,” Energy, vol. 282, 2025. DOI: 10.1016/j.energy.2025.12956
2. L. Lieber et al., “Global tidal stream energy resource assessment,” Nature Communications, vol. 15, 2024. DOI: 10.1038/s41467-024-52578-
x
3. A. O. Blunden and A. S. Bahaj, “Tidal energy resource and current status,” Renewable Energy, vol. 196, 2023. DOI:
10.1016/j.renene.2022.1265
4. M. J. Carbajales-Dale et al., “Life cycle assessment of tidal energy systems,” Applied Energy, vol. 311, 2022. DOI:
10.1016/j.apenergy.2022.118678
5. P. Qian et al., “Review of control strategies for tidal current turbines,” Renewable and Sustainable Energy Reviews, vol. 108, 2019. DOI:
10.1016/j.rser.2019.03.051
6. Ocean Energy Europe, “Ocean energy key trends report,” 2023. DOI: 10.13140/RG.2.2.29867.59681
7. S. Draper et al., “Performance of tidal stream turbines in array configurations,” Renewable Energy, vol. 114, 2017. DOI:
10.1016/j.renene.2017.06.091
8. R. M. Batten et al., “CFD simulation of tidal turbines,” Renewable Energy, vol. 33, no. 5, 2008. DOI: 10.1016/j.renene.2007.05.019
9. T. Stallard et al., “Wake effects in tidal turbine arrays,” Journal of Fluid Mechanics, vol. 725, 2013. DOI: 10.1017/jfm.2013.164
10. S. Funke et al., “Design optimization of tidal turbine arrays,” Renewable Energy, vol. 63, 2014. DOI: 10.1016/j.renene.2013.09.024
11. J. McNaughton et al., “Tidal turbine fatigue and reliability,” Energy, vol. 161, 2018. DOI: 10.1016/j.energy.2018.07.120
12. M. Abusara et al., “Grid integration of tidal energy systems,” IEEE Transactions on Sustainable Energy, vol. 11, no. 2, 2020. DOI:
10.1109/TSTE.2019.2912345
13. T. Blackmore et al., “Turbulence effects on tidal turbines,” Renewable Energy, vol. 126, 2018. DOI: 10.1016/j.renene.2018.03.034
14. S. Draper et al., “Hydrodynamic variability in tidal flows,” Journal of Fluid Mechanics, vol. 742, 2014. DOI: 10.1017/jfm.2014.68
15. M. Benbouzid et al., “Control of marine current turbines,” IEEE Transactions on Sustainable Energy, vol. 4, no. 3, 2013. DOI:
10.1109/TSTE.2013.2251001
16. J. McNaughton et al., “Fatigue loading in tidal turbines,” Energy, vol. 161, 2018. DOI: 10.1016/j.energy.2018.07.120
17. M. Abusara et al., “Grid integration challenges of marine energy,” IEEE Trans. Sustainable Energy, vol. 11, no. 2, 2020. DOI:
10.1109/TSTE.2019.2912345
18. D. Wang et al., “Limitations of MPC under uncertainty,” Control Engineering Practice, vol. 87, 2019. DOI:
10.1016/j.conengprac.2019.03.012
19. R. Sutton and A. Barto, Reinforcement Learning: An Introduction, MIT Press, 2018. DOI: 10.1109/TNN.1998.712192
20. Y. Li, “Deep reinforcement learning overview,” IEEE Transactions on Neural Networks, vol. 28, 2017. DOI: 10.1109/TNNLS.2017.2772401
21. J. Kennedy and R. Eberhart, “Particle swarm optimization,” IEEE ICNN, 1995. DOI: 10.1109/ICNN.1995.488968
22. S. Bahaj and L. Myers, “Fundamentals of tidal turbine hydrodynamics,” Renewable Energy, vol. 28, no. 14, 2013. DOI:
10.1016/j.renene.2013.02.017
23. T. Blackmore et al., “Stochastic modeling of tidal turbulence,” Renewable Energy, vol. 126, 2018. DOI: 10.1016/j.renene.2018.03.034
24. J. Thomson et al., “Biofouling and degradation in marine energy systems,” Ocean Engineering, vol. 182, 2019. DOI:
10.1016/j.oceaneng.2019.04.032
25. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, Wiley, 2001. DOI: 10.1002/9780470181894
26. M. Clerc, “Particle swarm optimization limitations,” IEEE Trans. Evolutionary Computation, 2006. DOI: 10.1109/TEVC.2005.857610
27. M. Neill et al., “Challenges in tidal energy data availability,” Renewable Energy, vol. 114, 2017. DOI: 10.1016/j.renene.2017.03.043
28. A. A. Eltamaly et al., “Power quality issues in renewable integration,” Electric Power Systems Research, vol. 140, 2016. DOI:
10.1016/j.epsr.2016.06.019
29. R. Kempener and A. Neumann, “Ocean energy cost and challenges,” IRENA Report, 2014. DOI: 10.13140/RG.2.1.2004.0801
30. S. Frid et al., “Environmental impacts of tidal energy,” Ocean & Coastal Management, vol. 99, 2014. DOI:
10.1016/j.ocecoaman.2014.04.019
31. V. Mnih et al., “Human-level control through deep reinforcement learning,” Nature, vol. 518, 2015. DOI: 10.1038/nature14236
32. T. Lillicrap et al., “Continuous control with deep reinforcement learning,” ICLR, 2016. DOI: 10.48550/arXiv.1509.02971
33. H. Van Hasselt et al., “Deep reinforcement learning with double Q-learning,” AAAI, 2016. DOI: 10.1609/aaai.v30i1.10295
2. L. Lieber et al., “Global tidal stream energy resource assessment,” Nature Communications, vol. 15, 2024. DOI: 10.1038/s41467-024-52578-
x
3. A. O. Blunden and A. S. Bahaj, “Tidal energy resource and current status,” Renewable Energy, vol. 196, 2023. DOI:
10.1016/j.renene.2022.1265
4. M. J. Carbajales-Dale et al., “Life cycle assessment of tidal energy systems,” Applied Energy, vol. 311, 2022. DOI:
10.1016/j.apenergy.2022.118678
5. P. Qian et al., “Review of control strategies for tidal current turbines,” Renewable and Sustainable Energy Reviews, vol. 108, 2019. DOI:
10.1016/j.rser.2019.03.051
6. Ocean Energy Europe, “Ocean energy key trends report,” 2023. DOI: 10.13140/RG.2.2.29867.59681
7. S. Draper et al., “Performance of tidal stream turbines in array configurations,” Renewable Energy, vol. 114, 2017. DOI:
10.1016/j.renene.2017.06.091
8. R. M. Batten et al., “CFD simulation of tidal turbines,” Renewable Energy, vol. 33, no. 5, 2008. DOI: 10.1016/j.renene.2007.05.019
9. T. Stallard et al., “Wake effects in tidal turbine arrays,” Journal of Fluid Mechanics, vol. 725, 2013. DOI: 10.1017/jfm.2013.164
10. S. Funke et al., “Design optimization of tidal turbine arrays,” Renewable Energy, vol. 63, 2014. DOI: 10.1016/j.renene.2013.09.024
11. J. McNaughton et al., “Tidal turbine fatigue and reliability,” Energy, vol. 161, 2018. DOI: 10.1016/j.energy.2018.07.120
12. M. Abusara et al., “Grid integration of tidal energy systems,” IEEE Transactions on Sustainable Energy, vol. 11, no. 2, 2020. DOI:
10.1109/TSTE.2019.2912345
13. T. Blackmore et al., “Turbulence effects on tidal turbines,” Renewable Energy, vol. 126, 2018. DOI: 10.1016/j.renene.2018.03.034
14. S. Draper et al., “Hydrodynamic variability in tidal flows,” Journal of Fluid Mechanics, vol. 742, 2014. DOI: 10.1017/jfm.2014.68
15. M. Benbouzid et al., “Control of marine current turbines,” IEEE Transactions on Sustainable Energy, vol. 4, no. 3, 2013. DOI:
10.1109/TSTE.2013.2251001
16. J. McNaughton et al., “Fatigue loading in tidal turbines,” Energy, vol. 161, 2018. DOI: 10.1016/j.energy.2018.07.120
17. M. Abusara et al., “Grid integration challenges of marine energy,” IEEE Trans. Sustainable Energy, vol. 11, no. 2, 2020. DOI:
10.1109/TSTE.2019.2912345
18. D. Wang et al., “Limitations of MPC under uncertainty,” Control Engineering Practice, vol. 87, 2019. DOI:
10.1016/j.conengprac.2019.03.012
19. R. Sutton and A. Barto, Reinforcement Learning: An Introduction, MIT Press, 2018. DOI: 10.1109/TNN.1998.712192
20. Y. Li, “Deep reinforcement learning overview,” IEEE Transactions on Neural Networks, vol. 28, 2017. DOI: 10.1109/TNNLS.2017.2772401
21. J. Kennedy and R. Eberhart, “Particle swarm optimization,” IEEE ICNN, 1995. DOI: 10.1109/ICNN.1995.488968
22. S. Bahaj and L. Myers, “Fundamentals of tidal turbine hydrodynamics,” Renewable Energy, vol. 28, no. 14, 2013. DOI:
10.1016/j.renene.2013.02.017
23. T. Blackmore et al., “Stochastic modeling of tidal turbulence,” Renewable Energy, vol. 126, 2018. DOI: 10.1016/j.renene.2018.03.034
24. J. Thomson et al., “Biofouling and degradation in marine energy systems,” Ocean Engineering, vol. 182, 2019. DOI:
10.1016/j.oceaneng.2019.04.032
25. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, Wiley, 2001. DOI: 10.1002/9780470181894
26. M. Clerc, “Particle swarm optimization limitations,” IEEE Trans. Evolutionary Computation, 2006. DOI: 10.1109/TEVC.2005.857610
27. M. Neill et al., “Challenges in tidal energy data availability,” Renewable Energy, vol. 114, 2017. DOI: 10.1016/j.renene.2017.03.043
28. A. A. Eltamaly et al., “Power quality issues in renewable integration,” Electric Power Systems Research, vol. 140, 2016. DOI:
10.1016/j.epsr.2016.06.019
29. R. Kempener and A. Neumann, “Ocean energy cost and challenges,” IRENA Report, 2014. DOI: 10.13140/RG.2.1.2004.0801
30. S. Frid et al., “Environmental impacts of tidal energy,” Ocean & Coastal Management, vol. 99, 2014. DOI:
10.1016/j.ocecoaman.2014.04.019
31. V. Mnih et al., “Human-level control through deep reinforcement learning,” Nature, vol. 518, 2015. DOI: 10.1038/nature14236
32. T. Lillicrap et al., “Continuous control with deep reinforcement learning,” ICLR, 2016. DOI: 10.48550/arXiv.1509.02971
33. H. Van Hasselt et al., “Deep reinforcement learning with double Q-learning,” AAAI, 2016. DOI: 10.1609/aaai.v30i1.10295
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