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Include warnings about lack of validation of static yaw misalignment …
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…method (NREL#265)

* adding warnings about lack of validation of static yaw misalignment method in documentation

* updating changelog and version to 3.0.1
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ejsimley authored Dec 23, 2023
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3 changes: 3 additions & 0 deletions CHANGELOG.md
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# Changelog
All notable changes to this project will be documented in this file. If you make a notable change to the project, please add a line describing the change to the "unreleased" section. The maintainers will make an effort to keep the [Github Releases](https://github.com/NREL/OpenOA/releases) page up to date with this changelog. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).

## [3.0.1 - 2023-12-22]
- Includes warnings about limitations and lack of validation of static yaw misalignment method.

## v3.0 - 29 September 2023

Please see the [updated documentation](https://openoa.readthedocs.io/en/latest/index.html) for a complete overview of the new and improved OpenOA. Much will look familiar, but using the library should now be much more streamlined, and usage should be significantly faster.
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10 changes: 7 additions & 3 deletions examples/07_static_yaw_misalignment.ipynb
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"\n",
"If uncertainty quantification (UQ) is selected, static yaw misalignment is calculated multiple times using a Monte Carlo approach using randomly chosen power curve filtering parameters and randomly sampled time steps each iteration. The resulting distribution of yaw misalignment estimates is used to compute 95% confidence intervals around the mean yaw misalginment estimates.\n",
"\n",
"In this example, we will demonstrate static yaw misalignment detection both with and without UQ."
"In this example, we will demonstrate static yaw misalignment detection both with and without UQ.\n",
"\n",
"<div class=\"alert alert-block alert-info\">\n",
"\u26a0\ufe0f Warning: The Static Yaw Misalignment method in OpenOA is a relatively simple method that has not yet been validated using data from wind turbines with known static yaw misalignments. Therefore, the results should be treated with caution. One known issue is that the method currently relies on nacelle wind speed measurements to determine the power performance as a function of wind vane angle. If the measured wind speed is affected by the amount of yaw misalignment, potential biases can exist in the estimated static yaw misalignment values.\n",
"</div>"
]
},
{
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],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "oa-env",
"language": "python",
"name": "python3"
"name": "oa-env"
},
"language_info": {
"codemirror_mode": {
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2 changes: 1 addition & 1 deletion openoa/__init__.py
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__version__ = "3.0"
__version__ = "3.0.1"
"""
When bumping version, please be sure to also update parameters in sphinx/conf.py
"""
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14 changes: 14 additions & 0 deletions openoa/analysis/yaw_misalignment.py
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# detection and calibration of yaw misalignment," Renewable Energy, 160, 1217-1227, 2020.
# 5. L. Gao and J. Hong, “Data-driven yaw misalignment correction for utility-scale wind turbines,”
# J. Renewable Sustainable Energy, 13, 063302, 2021.
#
# WARNING: This is a relatively simple method that has not yet been validated using data from wind
# turbines with known static yaw misalignments. Therefore, the results should be treated with
# caution. One known issue is that the method currently relies on nacelle wind speed measurements
# to determine the power performance as a function of wind vane angle. If the measured wind speed
# is affected by the amount of yaw misalignment, potential biases can exist in the estimated static
# yaw misalignment values.

from __future__ import annotations

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6. The overall yaw misalignment is estimated as the average yaw misalignment over all wind
speed bins.
.. warning:: This is a relatively simple method that has not yet been validated using data from
wind turbines with known static yaw misalignments. Therefore, the results should be treated
with caution. One known issue is that the method currently relies on nacelle wind speed
measurements to determine the power performance as a function of wind vane angle. If the
measured wind speed is affected by the amount of yaw misalignment, potential biases can
exist in the estimated static yaw misalignment values.
Args:
plant (:obj:`PlantData`): A :py:attr:`openoa.plant.PlantData` object that has been validated
with at least :py:attr:`openoa.plant.PlantData.analysis_type` = "StaticYawMisalignment".
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10 changes: 7 additions & 3 deletions sphinx/examples/07_static_yaw_misalignment.ipynb
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"\n",
"If uncertainty quantification (UQ) is selected, static yaw misalignment is calculated multiple times using a Monte Carlo approach using randomly chosen power curve filtering parameters and randomly sampled time steps each iteration. The resulting distribution of yaw misalignment estimates is used to compute 95% confidence intervals around the mean yaw misalginment estimates.\n",
"\n",
"In this example, we will demonstrate static yaw misalignment detection both with and without UQ."
"In this example, we will demonstrate static yaw misalignment detection both with and without UQ.\n",
"\n",
"<div class=\"alert alert-block alert-info\">\n",
"\u26a0\ufe0f Warning: The Static Yaw Misalignment method in OpenOA is a relatively simple method that has not yet been validated using data from wind turbines with known static yaw misalignments. Therefore, the results should be treated with caution. One known issue is that the method currently relies on nacelle wind speed measurements to determine the power performance as a function of wind vane angle. If the measured wind speed is affected by the amount of yaw misalignment, potential biases can exist in the estimated static yaw misalignment values.\n",
"</div>"
]
},
{
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],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "oa-env",
"language": "python",
"name": "python3"
"name": "oa-env"
},
"language_info": {
"codemirror_mode": {
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4 changes: 3 additions & 1 deletion sphinx/index.rst
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* ``StaticYawMisalignment``: The StaticYawMisalignment routine estimates the static yaw misalignment
for individual wind turbines as a function of wind speed by comparing the estimated wind vane
angle at which power is maximized to the mean wind vane angle at which the turbines operate.
The routine includes uncertainty quantification.
The routine includes uncertainty quantification. **Warning: This method has not been validated
using data from wind turbines with known static yaw misalignments and the results should be
treated with caution.**

Lower-level "toolkit" modules are provided in the utils subpackage. These methods are used
throughout the analysis classes. They can also be used individually to support general wind plant
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