Recent research led by Luke Evans from the EPSRC and NERC Centre for Doctoral Training in Offshore Renewable Energy at the University of Edinburgh has shed light on a significant challenge in tidal energy resource assessment. The study, published in the journal Measurement: Sensors, addresses the issue of data interference from Acoustic Doppler Current Profilers (ADCPs), which are critical instruments used to measure water flow in tidal environments.
In tidal energy sites, multiple ADCPs are deployed to gauge the energy potential accurately. However, when these instruments operate simultaneously, they can interfere with each other, a phenomenon known as ‘cross-talk.’ This interference can lead to data corruption, complicating the assessment of energy yield from tidal turbines. Evans and his team conducted a measurement campaign as part of the ReDAPT project, placing two ADCPs upstream of an operational tidal turbine to evaluate the effectiveness of existing placement guidelines set forth by IEC 62600-200 for Power Performance Assessment (PPA).
The findings were notable: despite adherence to industry standards, approximately 15% of the data returned from the ADCPs was unreliable due to cross-talk. This research marks the first time such interference has been quantified in real-world conditions. Evans stated, “We identified for the first time interference throughout the campaign and quantified subsequent impact on estimates.”
To mitigate this issue, the team developed a sophisticated algorithm capable of removing around 90% of the corrupted measurements, resulting in a 7% variation in estimated Annual Energy Production (AEP). This advancement not only enhances the accuracy of energy yield assessments but also opens the door for improved deployment strategies in tidal energy projects.
The implications of this research extend beyond academic interest; they present significant commercial opportunities for the tidal energy sector. By refining the data collection process, energy companies can make more informed decisions about site viability, potentially increasing investment in tidal energy infrastructure. The ability to accurately assess energy yield is crucial for attracting financing and ensuring the economic feasibility of tidal energy projects.
As the industry moves towards more multi-sensor deployments, Evans’ algorithm offers a valuable tool for ensuring data integrity, which is essential for the growth of renewable energy sources. By choosing appropriate layouts for instrument deployment, companies can further minimize the risk of data interference.
This research not only enhances the scientific understanding of tidal energy assessment but also provides practical solutions that can lead to more reliable energy production forecasts. As the demand for clean energy continues to rise, innovations like these are vital for the advancement of the tidal energy sector and the broader renewable energy landscape.
