Classification and quantification of uncertainties for a tidal turbine power performance assessment
dc.contributor.advisor
Sellar, Brian
dc.contributor.advisor
Laibing, Jia
dc.contributor.advisor
Ashton, Ian
dc.contributor.advisor
Ingram, David
dc.contributor.author
Evans, Luke
dc.contributor.sponsor
Engineering and Physical Sciences Research Council (EPSRC)
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dc.contributor.sponsor
Natural Environment Research Council (NERC)
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dc.contributor.sponsor
European Marine Energy Centre (EMEC)
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dc.date.accessioned
2025-02-25T10:02:18Z
dc.date.available
2025-02-25T10:02:18Z
dc.date.issued
2025-02-25
dc.description.abstract
As part of the worldwide initiative to lower carbon emissions, renewable energy sources are playing a crucial
role in decarbonising our energy systems. Tidal energy, known for its reliability and predictability, is emerging
as a contributor to the expanding array of renewable energy sources. As the tidal industry advances towards
commercialisation and larger arrays reducing uncertainties is increasingly important.
Uncertainties around power production increase commercial risk. This thesis classifies and quantifies uncertainties in Power Performance Assessments (PPAs) and offers guidance for future deployments. It examines
uncertainties arising from data processing and flow variations, using in-situ measurements obtained from Acoustic
Doppler Current Profilers (ADCPs) situated in close proximity to an operational Tidal Energy Converter (TEC)
. At present developers often follow guidance from International Electrotechnical commission (IEC) Technical
Specification 62600-200, that provides recommended positioning of instruments relative to the turbine of two
types: in-line and adjacent, where in-line involves deploying separate instruments upstream and downstream of
the turbine, and adjacent involves placing an instrument to either side of the turbine, across the rotor plane.
The performance of two closely-located in-line ADCPs (spaced 45 m apart) was assessed, demonstrating their
ability to gather usable data in this layout. However, this work identified for the first time interference between
the ADCPs throughout the campaign and quantified subsequent impact on Annual Energy Prediction (AEP)
estimates. A method to remove data anomalies caused by interference between closely positioned ADCPs has
been developed and demonstrated, resulting in a 7% variation in estimated AEP.
It was found that instrument placement is critical. Whilst small differences in velocity were found for in-line ADCPs,
for adjacent ADCPs an uncertainty in AEP of 2.6% and 7.3% was measured for flood and ebb tides respectively.
Where the difference stems from flow structures causing measurement bias during the ebb tide. Results show
that for regions of high vertical shear, AEP estimates can be misrepresented by up to 2.3% and 5.5% under an
imposed vertical misalignment of 1 and 2 metres respectively.
TEC developers require knowledge of flow direction to design and operate turbines. A study on methods to
estimate characteristic flow directions found variation in direction of 1.2◦ when averages across the rotor plane
were considered and, 4◦ when only operational velocities were considered. The flow direction naturally evolves
over a tidal cycle resulting in non-yawing (nacelle rotation mechanism) TEC concepts being susceptible to off-axis
currents. A sensitivity study to misalignment was conducted and under 5◦
, 10◦ and 15◦ misalignment, the AEP
differed by 2%, 6% and 13% respectively.
The work highlights that the impact of TEC misalignment on AEP estimates is influenced by the rated velocity of
the TEC and the maximum velocity at the site, particularly affecting TECs rated close to or over the maximum flow
velocity. However, the work highlights that non-yawing TECs rated at least 10% below the maximum flow velocity
can still operate at full capacity even with a 25◦ misalignment. During periods of slow speeds (tidal velocities
at the Fall of Warness were found to exhibit a difference of approximately 30% between neap and spring tides)
misalignment is shown to become more important. The methodology of uncertainty analysis demonstrated in this thesis gives comprehensive instructions for PPA
of tidal devices, including instrument setup, data processing and accurate uncertainty estimates. Recognising
and dealing with uncertainties in measurements remains vital for tidal energy projects. By adopting the methods
outlined in this work, data integrity, accuracy, and dependability can be enhanced, resulting in better decision-making, improved evaluations of performance, and heightened investor trust within the tidal energy sector.
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dc.identifier.uri
https://hdl.handle.net/1842/43145
dc.identifier.uri
http://dx.doi.org/10.7488/era/5686
dc.language.iso
en
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dc.publisher
The University of Edinburgh
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dc.relation.hasversion
L. Evans, I. G. C. Ashton, and B. G. Sellar, “Tidal turbine power performance assessments following IEC TS 62600-200 using measured and modelled power outputs,” Renewable Energy, vol. 212, no. May, pp. 138–150, 2023. [Online]. Available: https://doi.org/10.1016/j.renene.2023.05.031
en
dc.relation.hasversion
L. Evans, I. G. C. Ashton, and B. G. Sellar, “Impact on energy yield of varying turbine designs under conditions of misalignment to the current flow,” Energies, vol. 16, no. 9, p. 3923, 5 2023. [Online]. Available: https://www.mdpi.com/1996- 1073/16/9/3923
en
dc.relation.hasversion
Luke Evans, Ian Ashton, Brian Sellar, 'On the utility of partially corrupted flow measurement data arising from adjacent acoustic Doppler current profilers for energy yield assessment', Measurement: Sensors 35 (2024) 101293
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dc.subject
tidal energy
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dc.subject
measuring uncertainty
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dc.subject
power performance assessment
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dc.subject
flow variations
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dc.subject
acoustic Doppler current profilers
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dc.subject
seabed acoustic instruments
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dc.subject
flow reference
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dc.subject
natural tidal flow fluctuations
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dc.title
Classification and quantification of uncertainties for a tidal turbine power performance assessment
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
EngD Doctor of Engineering
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