Meta‐heuristic optimisation approach for wave energy converter design by means of a stochastic hydrodynamic model
Abstract A methodology to automate the sizing of a wave energy converter (WEC) is presented. The preliminary design of WEC geometry is addressed as a mathematical program by means of a meta‐heuristic optimisation, which includes as key aspects the use of a multi‐objective differential evolutionary (...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-02-01
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| Series: | IET Renewable Power Generation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/rpg2.12021 |
| Summary: | Abstract A methodology to automate the sizing of a wave energy converter (WEC) is presented. The preliminary design of WEC geometry is addressed as a mathematical program by means of a meta‐heuristic optimisation, which includes as key aspects the use of a multi‐objective differential evolutionary (DE) algorithm and the implementation of a stochastic hydrodynamic model of the WEC. In this methodology, the WEC concept, the control strategy, the power take‐off characteristics and the location have been taken into consideration due to their strong influence on the WEC design. As a case example, a real project has been selected, and the methodology has been applied to two test locations. Stochastic models are used to handle irregular sea states and to obtain statistical information while reducing the calculation effort when compared to time‐domain models. The output derived from the proposed methodology is a set of feasible solutions so‐called Pareto frontier. These solutions can be used as inputs for a detailed design process. Data from real projects could be used to further develop the sizing methodology by improving the algorithm convergence, refining the requirements, or including new restrictions. |
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| ISSN: | 1752-1416 1752-1424 |