Welcome to the next installment in our search for an accurate, cost-effective, and reproducible method to assess the energy improvement from wind turbine upgrades.
In our last video, we talked about why we shouldn't use nacelle wind speed as our independent variable to measure power performance: upgrades can change the nacelle transfer function or the relationship between the nacelle wind speed and undisturbed or free stream wind speed upstream of the rotor. Here, we'll take a look at techniques that attempt to measure this free stream wind flow, namely using wind sensors like ground-based LiDAR, nacelle-based LiDAR (2-beam and 4-beam), an anemometer mounted on the turbine spinner, or anemometers mounted on a met tower.
These are typically used in the context of IEC 61400-12-1 power curve test to measure a turbine’s power curve against the warranted power curve provided by the turbine OEM. These met towers might be able to look at relative changes due to turbine upgrades as well.
Some of these techniques also attempt to overcome the high uncertainty or insufficient accuracy of the nacelle anemometer being a point measurement. In other words, ground-based LiDAR, 4-beam nacelle mounted LiDAR, and met towers with sensors mounted at multiple heights can usually measure some variability of the wind with height—that is, sheer and veer. But there are critical downsides that preclude their use in many situations:
So if we can't use nacelle power curves and we don't want to perform expensive power curve tests, where can we go next? We're not out of ideas yet, so be sure to follow along so you don't miss the rest.
- These sensors can be expensive and potentially temperamental, reducing their cost-effectiveness and reproducibility. For example, sensors on a met tower are rarely maintained after the power curve test is complete and LiDAR are expensive and require periodic maintenance.
- They're labor-intensive, as the equipment may need to be moved around the plant to perform the measurements for different turbines, since the sensors need to be relatively close to the turbines of interest.
- These tests are time-intensive. A measurement campaign must collect sufficient data in the baseline state to enable future comparison with the optimized state, meaning the upgrades need to be delayed until the baseline data is collected, which may result in loss of energy.
- These tests are also limited in terms of wind direction, as we can't use the measurements from a met tower and ground-based LiDAR if they are in the wake of another turbine or the wake of the test turbine itself.
- Lastly, results from these tests may still have high uncertainty or low accuracy due to noisy sensors, drifting calibrations, or the inability to capture differences in measurements—for example turbulence levels before and after an upgrade. High uncertainty means you'll only be able to assess relatively large changes in turbine performance. The IEC 61400-12-1 standard even allows for around a 1% drift in wind speed sensor calibration over the span of a test, which is about the same order of magnitude of the improvement that we'd be looking to detect from a wind turbine upgrade.