wind-up v1

[aclerc]

v0 is a single-method tool: it measures turbine-upgrade uplift with a binned power-curve, test-vs-reference method. v1 turns wind-up into a platform in which alternative uplift methods are pluggable and objectively benchmarked on synthetic datasets with known ground truth. The driving goals are accurate and precise results from short campaigns and richer conditional information about how an upgrade performs (uplift by wind speed, uplift in wakes vs free-stream, day vs night, by direction/stability, etc.).

Metrics:

• Campaign uplift P50 bias and spread
• Conditional uplift distribution: can measure per bin bias and spread of uplift distributions (vs wind speed, wind direction, TI, etc)
• Uncertainty quantification: harder to judge but can verify campaign uplift actual quantiles vs those implied by the reported uncertainty (eg verify that ground truth uplift is below P95 exactly 5% of the time)
• AEP uplift P50 bias and spread
  • A 'ground truth' AEP can be calculated if the source data has sufficient years. HOT has 5 clean years (2016-2020) so an AEP comparison based on those 5 years can be done. In this case the method estimates the AEP based on what it has learned about the uplift (conditional distribution) and the weather data it has access to (ERA5). However this is fairly tricky because even if the uplift is a very simple function of the turbine's conditions (eg just wind speed) the relationship between ERA5 data and the turbine's wind speed will usually be complicated (eg directional effect like wakes)
  • In some cases the AEP calculation will be done with a different tool (example FLORIS for wake steering, or pre-construction yield modelling could be used). In those cases wind-up needs to report out whatever these tools need. The vs wind speed conditional uplift distribution can be used to make a new power curve for pre-construction modelling, for example. FLORIS modelling would need more complex things like Pp (can be derived from uplift vs steer command) and perhaps wake model parameters.

Design considerations:

• Robustness to reference turbine changes. Reference turbine performance can change in time which introduces risk of bias. Reference turbine wind speed is even more likely to change in time (eg due to anemometer calibration change)