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Design and evaluation of linear and rotational generator scale models for wave tank testing
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity. Uppsala University. (Wave Power Group)ORCID iD: 0000-0002-1165-5569
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity. (Wave power group)
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity. (Wave power group)ORCID iD: 0000-0001-9213-6447
(Wave power group)ORCID iD: 0000-0002-2031-8134
2019 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
CRC Press , 2019.
National Category
Energy Systems Ocean and River Engineering Marine Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:uu:diva-457307ISBN: 9780429505324 (print)ISBN: 9781138585355 (electronic)OAI: oai:DiVA.org:uu-457307DiVA, id: diva2:1606493
Conference
3rd international conference on renewable energies offshore (renew 2018), 8–10 october 2018, Lisbon, Portugal
Available from: 2021-10-27 Created: 2021-10-27 Last updated: 2024-03-12Bibliographically approved
In thesis
1. Prediction horizon requirement  in control and extreme load analyses for survivability: Advancements to improve the performance of wave energy technologies
Open this publication in new window or tab >>Prediction horizon requirement  in control and extreme load analyses for survivability: Advancements to improve the performance of wave energy technologies
2021 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The main objective of wave energy converters (WECs) is to ensure reliable electricity production at a competitive cost. Two challenges to achieving this are ensuring an efficient energy conversion and offshore survivability.        

This thesis work is structured in three different sections: Control and maximum power optimization, forces and dynamics analysis in extreme wave conditions, and statistical modeling of extreme loads in reliability analysis.       

The need for prediction and future knowledge of waves and wave forces is essential due to the non-causality of the optimal velocity relation for wave energy converters. Using generic concepts and modes of motion, the sensitivity of the prediction horizon to various parameters encountered in a real system is elaborated. The results show that through a realistic assumption of the dissipative losses, only a few seconds to about half a wave cycle is sufficient to predict the required future knowledge for the aim of maximizing the power absorption.         

The results of a 1:30 scaled wave tank experiment are used to assess the line force and dynamic behaviour of a WEC during extreme wave events. Within the comparison of different wave type representations, i.e. irregular, regular and focused waves, of the same sea state, the results show that not all the wave types deliver the same maximum line forces. As a strategy of mitigating the line forces during extreme wave events, changing the power take-off (PTO) damping may be employed. With consideration of the whole PTO range, the results indicate an optimum damping value for each sea state in which the smallest maximum line force is obtained. Although wave breaking slamming and end-stop spring compression lead to high peak line forces, it is possible that they level out due to the overtopping effect. Waves with a long wavelength result in large surge motion and consequently higher and more damaging forces.        

On the investigation of reliability assessment of the wave energy converter systems, computing the return period of the extreme forces is crucial. Using force measurement force data gathered at the west coast of Sweden, the extreme forces are statistically modelled with the peak-over-threshold method. Then, the return level of the extreme forces over 20 years for the calm season of the year is computed.

Place, publisher, year, edition, pages
Uppsala: Uppsala University, 2021. p. 70
Keywords
control, optimal velocity, non-causality, maximum power output, extreme waves, wave tank experiment, end-stop compression, wave breaking slamming, PTO damping, return level, return period, peak-over-threshold
National Category
Energy Systems Marine Engineering Control Engineering Ocean and River Engineering Energy Engineering
Identifiers
urn:nbn:se:uu:diva-457329 (URN)
Presentation
2021-12-17, Häggsalen, Ångström Laboratory, Lägerhyddsvägen 1, Uppsala, 10:00 (English)
Supervisors
Available from: 2021-11-25 Created: 2021-10-27 Last updated: 2021-11-25Bibliographically approved
2. Survivability control using data-driven approaches and reliability analysis for wave energy converters
Open this publication in new window or tab >>Survivability control using data-driven approaches and reliability analysis for wave energy converters
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Wave energy, with five times the energy density of wind and ten times the power density of solar, offers a compelling carbon-free electricity solution. Despite its advantages, ongoing debates surround the reliability and economic feasibility of wave energy converters (WECs). To address these challenges, this doctoral thesis is divided into four integral parts, focusing on optimizing the prediction horizon for power maximization, analyzing extreme waves' impact on system dynamics, ensuring reliability, and enhancing survivability in WECs.

Part I emphasizes the critical importance of the prediction horizon for maximal power absorption in wave energy conversion. Using generic body shapes and modes, it explores the effect of dissipative losses, noise, filtering, amplitude constraints, and real-world wave parameters on the prediction horizon. Findings suggest achieving optimal power output may be possible with a relatively short prediction horizon, challenging traditional assumptions.

Part II shifts focus to WEC system dynamics, analyzing extreme load scenarios. Based on a 1:30 scaled wave tank experiment, it establishes a robust experimental foundation, extending into numerical assessment of the WEC. Results underscore the importance of damping to alleviate peak forces. Investigating various wave representations highlights conservative characteristics of irregular waves, crucial for WEC design in extreme sea conditions.

Part III explores the computational intricacies of environmental design load cases and fatigue analyses for critical mechanical components of the WEC. The analysis is conducted for hourly sea state damage and equivalent two-million-cycle loads. Finally, a comparison of safety factors between the ultimate limit state and fatigue limit state unfolds, illustrating the predominant influence of the ultimate limit state on point-absorber WEC design.

Part IV, centers on elevating survivability strategies for WECs in extreme wave conditions. Three distinct controller system approaches leverage neural networks to predict and minimize the line force. Distinct variations emerge in each approach, spanning from rapid detection of optimal damping to integrating advanced neural network architectures into the control system with feedback. The incorporation of a controller system, refined through experimental data, showcases decreases in the line force, providing a practical mechanism for real-time force alleviation.

This thesis aims to contribute uniquely to the goal of advancing wave energy conversion technology through extensive exploration.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2024. p. 169
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 2377
Keywords
power maximization, prediction horizon, extreme wave conditions, wave tank experiment, numerical WEC-Sim analysis, reliability analysis, statistical methods, environmental design load, fatigue analysis, statistical methods, survivability analysis, neural network methods
National Category
Control Engineering Energy Systems Ocean and River Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering Marine Engineering Reliability and Maintenance Energy Engineering
Identifiers
urn:nbn:se:uu:diva-524903 (URN)978-91-513-2077-9 (ISBN)
Public defence
2024-05-17, Häggsalen (10132), Ångströmlaboratoriet, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2024-04-22 Created: 2024-03-12 Last updated: 2024-04-22

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Shahroozi, ZahraEriksson, MikaelGöteman, MalinEngström, Jens

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