diff --git a/_sources/overview.rst b/_sources/overview.md similarity index 71% rename from _sources/overview.rst rename to _sources/overview.md index 639f8e15..547df5b9 100644 --- a/_sources/overview.rst +++ b/_sources/overview.md @@ -1,25 +1,25 @@ -Overview --------- +# Overview + FLASC provides a rich suite of analysis tools for SCADA data filtering & analysis, wind farm model validation, field experiment design, and field experiment monitoring. The repository is centrally built around NRELs -in-house `floris `_ wake modeling utility. +in-house [floris](https://github.com/nrel/floris) wake modeling utility. FLASC also largely relies on the energy ratio to, among others, quantify wake losses in synthetic and historical data, to perform turbine northing calibrations, and for model parameter estimation. -Literature -========== -See :cite:`Doekemeijer2022a` and :cite:`Bay2022a` for a practical +# Literature + +See a particular wind rose, e.g., for annual operation. See +{cite:p}`Doekemeijer2022a` and {cite:p}`Bay2022a`for a practical example of how the flasc repository is used or processing and analyses of historical SCADA data of three offshore wind farms. - .. bibliography:: references.bib - :style: unsrt - :filter: docname in docnames + ```{bibliography} + ``` + +# Citation -Citation -======== If FLASC played a role in your research, please cite it. This software can be cited as: @@ -28,7 +28,6 @@ cited as: For LaTeX users: -.. code-block:: latex @misc{flasc2022, author = {NREL}, @@ -40,47 +39,40 @@ For LaTeX users: } -Questions -========= +# Questions + For technical questions regarding FLASC usage, please post your questions to -`GitHub Discussions `_ on the +[GitHub Discussions](https://github.com/NREL/flasc/discussions) on the FLASC repository. Alternatively, email the NREL FLASC team at `paul.fleming@nrel.gov `_ or `michael.sinner@nrel.gov `_. -Module overview -================= +# Module overview + FLASC consists of multiple modules, including: -++++++++++++++++++++++++++ -flasc.dataframe_operations -++++++++++++++++++++++++++ + +## flasc.dataframe_operations + This module includes functionality to easily manipulate Pandas DataFrames. Functions include filtering data by wind direction, wind speed an/or TI, deriving the ambient conditions from the upstream turbines, all the while dealing with angle wrapping for angular variables. -++++++++++++++++++++++++++ -flasc.energy_ratio -++++++++++++++++++++++++++ + +## flasc.energy_ratio + this module contains classes to calculate and visualize the energy ratio as defined by Fleming et al. (2019). The energy ratio is a very useful quantity in SCADA data analysis and related model validation. It represents the amount of energy produced by a turbine relative to what that turbine would have -produced if no wakes were present. Various classes are included in this model, -from classes used to calculate and plot the energy ratio for a single dataset, -a class for multiple datasets, and a class that calculates the wind direction -bias for every turbine by maximizing the energy ratio fit between FLORIS and -SCADA data. Various visualization methods are included such as energy ratio -plots and automated generation of detailed excel spreadsheets to determine -where and which turbines performed differently than expected. These methods -can be used both for model validation and for processing field campaign data, -e.g. baseline vs optimized operation. - -++++++++++++++++++++++++++ -flasc.floris_tools -++++++++++++++++++++++++++ +produced if no wakes were present. See [energy ratio](energy_ratio) for more +details. + + +## flasc.floris_tools + This module contains functions that leverage the floris model directly. This includes functions to calculate a large set of floris simulations (with MPI, optionally) for different atmospheric conditions, yaw misalignments and/or @@ -88,18 +80,18 @@ model parameters. It also includes two functions to precalculate and respectively interpolate from a large set of model solutions to speed up further postprocessing. -++++++++++++++++++++++++++ -flasc.model_estimation -++++++++++++++++++++++++++ + +## flasc.model_estimation + This is a module related to the estimation of parameters in the floris wind farm model. One class herein, called floris_sensitivity_analysis, performs Sobol parameter sensitivity studies to determine which parameters are most sensitive in various situations (atmospheric conditions, turbine settings, wind farm layouts). -++++++++++++++++++ -flasc.optimization -++++++++++++++++++ + +## flasc.optimization + The optimization module includes functions to estimate the timeshift between two sources of data, for example, to sychronize measurements from a met mast with measurements from SCADA data. The module also includes a function to @@ -109,9 +101,9 @@ correct calibration of at least one other wind turbine. Finally, this module also contains a function to estimate the atmospheric turbulence intensity based on the power measurements of the turbines inside a wind farm. -+++++++++++++++++++++++ -flasc.raw_data_handling -+++++++++++++++++++++++ + +## flasc.raw_data_handling + This module contains functions that supports importing and processing raw SCADA data files. Specifically, it provides a class called "sql_database_manager" which can be used to up- and download data between @@ -122,9 +114,9 @@ format for optimal balance of storage size and load/write speed. Additionally, can split one large dataframe into multiple dataframes and feather files. -+++++++++++++++++++++++ -flasc.time_operations -+++++++++++++++++++++++ + +## flasc.time_operations + This module allows the user to easily downsample, upsample and calculate moving averages of a data frame with SCADA and/or FLORIS data. These functions allow the user to specify which columns contain angular variables, and @@ -132,11 +124,9 @@ consequently 360 deg wrapping is taken care of. It also allows the user to calculate the min, max, std and median for downsampled data frames. It leverages efficient functions inherent in pandas to maximize performance. -+++++++++++++++++++++++ -flasc.turbine_analysis -+++++++++++++++++++++++ + +## flasc.turbine_analysis + this module allows the user to analyze SCADA data on a turbine level. Outliers can be detected and removed. Filtering methods include sensor-stuck type of fault detection and analysis of the turbine wind speed-power curve. - -.. seealso:: `Return to table of contents `_ diff --git a/overview.html b/overview.html index 87c37fc5..a486f5bb 100644 --- a/overview.html +++ b/overview.html @@ -271,7 +271,7 @@

FLASC

  • - FLASC