Edinburgh Research Archive

Classification and quantification of uncertainties for a tidal turbine power performance assessment

Item Status

Embargo End Date

Authors

Evans, Luke

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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