Imperial College London
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Stephan Kramer

Faculty of Engineering, Department of Earth Science & Engineering

Advanced Research Fellow
 
 
 
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Contact

 

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Location

 

4.85Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Culley:2017:10.1016/j.ijome.2017.05.001,
author = {Culley, DM and Funke, SW and Kramer, SC and Piggott, MD},
doi = {10.1016/j.ijome.2017.05.001},
journal = {International Journal of Marine Energy},
pages = {357--373},
title = {A surrogate-model assisted approach for optimising the size of tidal turbine arrays},
url = {http://dx.doi.org/10.1016/j.ijome.2017.05.001},
volume = {19},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The new and costly nature of tidal stream energy extraction technologies can lead to narrow margins of success for a project. The design process is thus a delicate balancing act – to maximise the energy energy extracted, while minimising cost and risk. Scenario specific factors, such as site characteristics, technological constraints and practical engineering considerations greatly impact upon both the appropriate number of turbines to include within a tidal current turbine array (array size), and the individual locations of those turbines (turbine micro-siting). Both have been shown to significantly impact upon the energy yield and profitability of an array.The micro-siting arrangement for a given number of turbines can significantly influence the power extraction of a tidal farm. Until the layout has been optimised (a process which may incorporate turbine parameters, local bathymetry and a host of other practical, physical, legal, financial or environmental constraints) an accurate forecast of the yield of that array cannot be determined. This process can be thought of as ‘tuning’ an array to the proposed site to maximise desirable outcomes and mitigate undesirable effects.The influence of micro-siting on the farm performance means that determining the optimal array size needs to be coupled to the micro-siting process. In particular, the micro-siting needs to be repeated for any new trial array size in order to be able to compare the performance of the different farm sizes. Considering the large number of design variables in the micro-siting problem (which includes at least the positions of each turbine) it becomes clear that algorithmic optimisation is a key tool to rigorously determine the optimal array size and layout.This paper proposes a nested optimisation approach for solving the array size and layout problem. The core of this approach consists of two nested optimisation procedures. The ‘outer’ optimisation determines the array
AU  - Culley,DM
AU  - Funke,SW
AU  - Kramer,SC
AU  - Piggott,MD
DO  - 10.1016/j.ijome.2017.05.001
EP  - 373
PY  - 2017///
SN  - 2214-1669
SP  - 357
TI  - A surrogate-model assisted approach for optimising the size of tidal turbine arrays
T2  - International Journal of Marine Energy
UR  - http://dx.doi.org/10.1016/j.ijome.2017.05.001
UR  - http://hdl.handle.net/10044/1/49365
VL  - 19
ER  -
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