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Environmental design load for the line force of a point-absorber wave energy converter
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity.ORCID iD: 0000-0002-1165-5569
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity. Centre of Natural Hazards and Disaster Science (CNDS), Villavägen 16, Uppsala, 752 36, Sweden.ORCID iD: 0000-0001-9213-6447
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL. Centre of Natural Hazards and Disaster Science (CNDS), Villavägen 16, Uppsala, 752 36, Sweden. (Meteorologi)ORCID iD: 0000-0003-3740-9507
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity.ORCID iD: 0000-0002-2031-8134
2022 (English)In: Applied Ocean Research, ISSN 0141-1187, E-ISSN 1879-1549, Vol. 128, article id 103305Article in journal (Refereed) Published
Abstract [en]

To ensure a reliable operation over the life time of wave energy converters (WECs), a number of load cases need to be considered according to international standards for marine structures to determine an optimal design. This paper outlines the procedure of obtaining an environmental design load for the line force of a 1:30 scaled point-absorber WEC using an environmental contour with a 50-year return period for the Dowsing site in the North Sea. To obtain the response of the WEC during extreme conditions, a numerical WEC-Sim model is developed and calibrated with experimental wave tank tests to augment the data required for such design load analysis. The design load for the line force is estimated based on the full long-term extreme response computed from the full sea state approach by considering 180, 360, and 720 sea state samples as well as the contour approach for the sea state that gives the most extreme response. Further, a probabilistic approach is used to quantify the probability of failure for a critical mechanical component of the system such as shackle. The result shows that the numerical WEC-Sim model is able to sufficiently replicate the real response of the system during extreme irregular waves. The Bayesian theory with Monte-Carlo algorithm is found to be an excellent tool for identifying the degree of belief in the statistical models used for the short-term extreme response analysis. Considering the ultimate limit state, the design load for the 1:30 scaled system is calculated as 670.95 N (i.e. 18.11 MN for a full-scale system) after applying the partial load safety factor of 1.35 on the full long-term extreme response of the system for the 9.1 years return period (i.e. 50 years in a full-scale model).

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 128, article id 103305
Keywords [en]
Design load, Wave tank experiment, WEC-Sim, Bayesian, Markov chain Monte-Carlo, Long-term extreme response, Short-term extreme response, Probabilistic failure
National Category
Energy Engineering Reliability and Maintenance Marine Engineering
Identifiers
URN: urn:nbn:se:uu:diva-484405DOI: 10.1016/j.apor.2022.103305ISI: 000857872300005OAI: oai:DiVA.org:uu-484405DiVA, id: diva2:1694898
Funder
Swedish Energy Agency, 47264-1Swedish Research Council, 2020-03634Swedish Research Council Formas, 2018-01784Available from: 2022-09-12 Created: 2022-09-12 Last updated: 2024-03-12Bibliographically approved
In thesis
1. 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, ZahraGöteman, MalinEngström, Jens

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