On the utility of partially corrupted flow measurement data arising from adjacent acoustic Doppler current profilers for energy yield assessment

Recommended practice for quantifying the energy resource at a tidal energy site requires the use of multiple instruments deployed across the site. However, the instruments used work by emitting an acoustic pulse and instruments working at the same time have the potential to interfere with each other through a process known as ’cross-talk’. It is important to understand the impact of cross-talk on measurements and how this can be managed and through data processing or suitable positioning of devices. The ReDAPT project conducted a measurement campaign using two Acoustic Doppler Current Profilers (ADCPs) placed upstream of an operational tidal turbine. This aimed to assess the ’in-line’ instrument placement guidelines from IEC 62600-200 for Power Performance Assessment (PPA) in real-world conditions. Consequently, the results within hold potential to support arguments for expanding these zones or adjusting their general dimensions. Despite adhering to industry standards and best practices to eliminate unreliable data in the Quality Control (QC) checks, in both concurrently measuring ADCPs at different time stamps in approximately 15 % of the returned data. This work identified for the first time interference throughout the campaign and quantified subsequent impact on 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 Annual Energy Production (AEP). The algorithm effectively removed approximately 90 % of the corrupted measurements. Moving forward, multi-sensor deployments could use the algorithm described to double-check for interference within the data sets, although care should be taken to avoid this by choosing a suitable layout for deployment. • Proximal ADCPs (45 m apart) in energetic tidal channel without sampling synchronisation results in periods of data corruption. • Visual inspection revealed anomalies in auto-checked data. A developed algorithm identifies corrupted data with 90 % accuracy. • Configuration yields valid data and provides insights for tidal energy and broader multi-sensor deployments. • AEP estimates for three turbine types showed 2–7% variation after anomalous data removal, more notably near sea surface.