openfast-service

A simple wrapper around OpenFAST to run it as a cloud service.

The docs are built automatically, and hosted at: https://windenergie-hsr.gitlab.io/aerosense/digital-twin/fsi-twins/openfast-service/

OpenFAST

OpenFAST Docs: https://openfast.readthedocs.io

OpenFAST compiled executable

Can be compiled from source: https://github.com/OpenFAST/OpenFAST or installed from conda forge: conda install -c conda-forge openfast

Regression Tests

Regression tests are currently at: https://github.com/OpenFAST/r-test

Controller DLLs:

Before running some tests, the controller DLL should be compiled for your system. DISCON controller comes with source code and makefiles. To build DISCON on the LINUX system use:

cmake DISCON
make

OpenFAST Models of the wind turbines:

NREL Wind Turbine Models can be found at: https://github.com/NREL/openfast-turbine-models/

OpenFAST Tools

https://github.com/OpenFAST/python-toolbox

OpenFAST Service Infrastructure

TODO this should probably go in the docs, chucking it here for now:

The Question

Initially, we wanted to make the OpenFAST Service as simple as possible for a proof-of-concept. To do achieve that, we need to decide - what is the question we're trying to answer? We will, of course, evolve the service from this point, to become a much more general simulator of turbine performance.

Question 1 For a given 10 minute period of the Aventa turbine, at the Aventa site, what is the power output and base bending moment?

Why do we want to know this? So that we can compare those results with measured values from the turbine.

Question 2 For a given 10 minute period of the Aventa turbine operation, what is the rotor-angle-averaged averaged AoA over that period (for, say 36 angular positions)?

Why do we want to know this? So that for polar inputs which are not derived from aerosense measurements, we can compare these outputs with rotor-angle-averaged AoA from the Aerosense system as validation.

Inputs

Input files: Turbine Model Dataset

- We will have a bucket in the aerosense project for turbine models.
- Each turbine model has a folder, named sensibly e.g. `aventa-prototype-whatever` which will be the key of our turbine model
- A turbine model dataset is a collection of files representing a turbine, and will roughly consist of:
    - Aerodynamics file (including specified path to separate folder for aerofoil polars)
    - Blades file
    - Tower file
    - Structural properties files
    - Main input file
    - Controller .so file

Input values

A detailed overview of openFAST inputs is available here. We distil most of them into the specific turbine model, but supply some here as the main parameters of the service, enabling the questions to be asked with varying parameters.

• Inflow wind speed

  • TODO Determine hub_height parameter from the input model

• cl, cd polars

  • A polar is a graph, basically, of lift vs drag over a range of alpha (angle of attack)
  • Polars can come from 2d cfd, aerosense measurements, wind tunnel measurements
  • TODO if trying to drive openFAST with polars derived from aerosense, we only have three stations. This won't give a robust distribution of polars across the blade. Either we need to robustly interp/extrap within this service, or we need to interp/extrap from aerosense results prior to calling openFAST with them.

• Aerosense sensor radii locations for AoA measurement

• Turbulence generator input data

Output values

• 10-minute timeseries of Turbine power and thrust coefficients (array of two tuples CP and CT [no units])
• 10-minute timeseries of Tower base bending moments (array of six tuples Fx, Fy, Fz, Mx, My, Mz [N])
• Measurements are sampled at 10/100Hz for 10 minutes, so we should match this dataset in form
• Rotor-angle-averaged AoA at sensor locations (for comparison with AoAs calculated)

Building documents manually

If you did need to build the documentation

Install doxgen. On a mac, that's brew install doxygen; other systems may differ.

Install sphinx and other requirements for building the docs:

pip install -r docs/requirements.txt

Run the build process:

sphinx-build -b html docs/source docs/build