3. ROSCO Examples

Methods for reading turbine models, generating the control parameters of a DISCON.IN: file, and running aeroelastic simulations to test controllers Reading Turbine Models ———————- Control parameters depend on the turbine model. The rosco.toolbox uses OpenFAST inputs and an additional .yaml formatted file to set up a turbine object in python. Several OpenFAST inputs are located in Test_Cases/. The controller tuning .yaml are located in Tune_Cases/. A detailed description of the ROSCO control inputs and tuning .yaml are provided in The DISCON.IN file and ROSCO_Toolbox tuning .yaml, respectively.

  • 01_turbine_model.py loads an OpenFAST turbine model and displays a summary of its information

ROSCO requires the power and thrust coefficients for tuning control inputs and running the extended Kalman filter wind speed estimator.

  • 02_ccblade.py runs cc-blade, a blade element momentum solver from WISDEM, to generate a \(C_p\) surface.

The Cp_Cq_Ct.txt (or similar) file contains the rotor performance tables that are necessary to run the ROSCO controller. This file can be located wherever you desire, just be sure to point to it properly with the PerfFileName parameter in DISCON.IN.

3.1. Tuning Controllers and Generating DISCON.IN

The ROSCO turbine object, which contains turbine information required for controller tuning, along with control parameters in the tuning yaml and the \(C_p\) surface are used to generate control parameters and DISCON.IN files. To tune the PI gains of the torque control, set omega_vs and zeta_vs in the yaml. Similarly, set omega_pc and zeta_pc to tune the PI pitch controller; gain scheduling is automatically handled using turbine information. Generally omega_* increases the responsiveness of the controller, reducing generator speed variations, but an also increases loading on the turbine. zeta_* changes the damping of the controller and is generally less important of a tuning parameter, but could also help with loading. The default parameters in Tune_Cases/ are known to work well with the turbines in this repository.

  • 03_tune_controller.py loads a turbine and tunes the PI control gains

  • 04_simple_sim.py tunes a controller and runs a simple simualtion (not using OpenFAST)

  • 05_openfast_sim.py loads a turbine, tunes a controller, and runs an OpenFAST simulation

Each of these examples generates a DISCON.IN file, which is an input to libdiscon.*. When running the controller in OpenFAST, DISCON.IN must be appropriately named using the DLL_FileName parameter in ServoDyn.

OpenFAST can be installed from source or in a conda environment using:

conda install -c conda-forge openfast

ROSCO can implement peak shaving (or thrust clipping) by changing the minimum pitch angle based on the estimated wind speed:

  • 06_peak_shaving.py loads a turbine and tunes a controller with peak shaving.

By setting the ps_percent value in the tuning yaml, the minimum pitch versus wind speed table changes and is updated in the DISCON.IN file.

ROSCO also contains a method for distributed aerodynamic control (e.g., via trailing edge flaps):

  • 09_distributed_aero.py tunes a controller for distributed aerodynamic control

The ROSCO toolbox also contains methods for working with OpenFAST linear models * 10_linear_params.py exports a file of the parameters used for the simplified linear models used to tune ROSCO * 11_robust_tuning.py shows how linear models generated using OpenFAST can be used to tune controllers with robust stability properties. * 12_tune_ipc.py shows the tuning procedure for IPC

3.2. Running OpenFAST Simulations

To run an aeroelastic simulation with ROSCO, the ROSCO input (DISCON.IN) must point to a properly formatted Cp_Cq_Ct.txt file using the PerfFileName parameter. If called from OpenFAST, the main OpenFAST input points to the ServoDyn input, which points to the DISCON.IN file and the libdiscon.* dynamic library.

For example in Test_Cases/NREL-5MW:

  • NREL-5MW.fst has "NRELOffshrBsline5MW_Onshore_ServoDyn.dat" as the ServoFile input

  • NRELOffshrBsline5MW_Onshore_ServoDyn.dat has "../../ROSCO/build/libdiscon.dylib" as the DLL_FileName input and "DISCON.IN" as the DLL_InFile input. Note that these file paths are relative to the path of the main fast input (NREL-5MW.fst)

  • DISCON.IN has "Cp_Ct_Cq.NREL5MW.txt" as the PerfFileName input

The rosco.toolbox has methods for running OpenFAST (and other) binary executables using system calls, as well as post-processing tools in ofTools/.

Several example scripts are set up to quickly simulate ROSCO with OpenFAST:

  • 05_openfast_sim.py loads a turbine, tunes a controller, and runs an OpenFAST simulation

  • 07_openfast_outputs.py loads the OpenFAST output files and plots the results

  • 08_run_turbsim.py runs TurbSim, for generating turbulent wind inputs

  • 14_open_loop_control.py runs an OpenFAST simulation with ROSCO providing open loop control inputs

3.3. Testing ROSCO

The rosco.toolbox also contains tools for testing ROSCO in IEC design load cases (DLCs), located in ROSCO_testing/. The script run_Testing.py allows the user to set up their own set of tests. By setting testtype, the user can run a variety of tests:

  • lite, which runs DLC 1.1 simulations at 5 wind speed from cut-in to cut-out, in 330 second simulations

  • heavy, which runs DLC 1.3 from cut-in to cut-out in 2 m/s steps and 2 seeds for each, in 630 seconds, as well as DLC 1.4 simulations

  • binary-comp, where the user can compare libdiscon.* dynamic libraries (compiled ROSCO source code), with either a lite or heavy set of simulations

  • discon-comp, where the user can compare DISCON.IN controller tunings (and the complied ROSCO source is constant)

Setting the turbine2test allows the user to test either the IEA-15MW with the UMaine floating semisubmersible or the NREL-5MW reference onshore turbine.

3.4. List of Examples

A complete list of examples is given below:

3.4.1. 01_turbine_model

Interact with a ROSCO turbine model:

  • Read .yaml input file

  • Load an openfast turbine model

  • Read text file with rotor performance properties (Cp, Ct, and Cq surface)

  • Print some basic turbine properties

  • Save the turbine as a pickle

  • Plot the Cp surface

../_images/01_NREL5MW_Cp.png

Note: Uses the NREL 5MW included in the Test Cases and is a part of the OpenFAST distribution

3.4.2. 02_ccblade

Run CCblade, save a rotor performance text file. In this example:

  • Read .yaml input file

  • Load an openfast turbine model

  • Run ccblade to get rotor performance properties

  • Write a text file ('02_Cp_Ct_Cq.Ex03.txt') with rotor performance properties

3.4.3. 03_tune_controller

Load a turbine model and tune the controller In this example:

  • Read a .yaml file

  • Create a ROSCO turbine object fromt he OpenFAST model

  • Tune a ROSCO controller object

  • Write a controller input file ('03_DISCON.IN')

  • Plot gain schedule (PC_GS_KP and PC_GS_KI versus PS_GS_angles):

../_images/03_GainSched.png

3.4.4. 04_simple_sim

Demonstrate the simple 1-DOF wind turbine simulator with ROSCO

In this example:

  • Load turbine from saved pickle and tune a ROSCO controller

  • Run and plot a step wind simulation using 1-DOF model in rosco.toolbox.sim and the ROSCO dynamic library

../_images/04_NREL5MW_SimpSim.png

Notes:

  • You must have a compiled controller in ROSCO/rosco/lib/, and properly point to it using the lib_name variable.

  • Using wind speed estimators in this simple simulation is known to cause problems. We suggest using WE_Mode = 0 in the DISCON.IN or increasing sampling rate of simulation as workarounds.

  • The simple simulation is run twice to check that arrays are deallocated properly.

3.4.5. 05_openfast_sim

Load a turbine, tune a controller, and run an OpenFAST simulation. In this example:

  • Load a turbine from OpenFAST

  • Tune a controller

  • Run an OpenFAST simulation

Note

  • You must have a compiled controller in ROSCO/rosco/lib/

3.4.6. 06_peak_shavings

Load saved turbine, tune controller, plot minimum pitch schedule In this example:

  • Load a yaml file

  • Load a turbine from openfast

  • Tune a controller

  • Plot minimum pitch schedule

3.4.7. 07_openfast_outputs

Plot some OpenFAST output data In this example:

  • Load openfast output data

  • Trim the time series

  • Plot some available channels

Note: need to run openfast model in ‘Test_Cases/5MW_Land_DLL_WTurb/’ to plot

3.4.8. 08_run_turbsim

Run TurbSim to create wind field binary In this example:

  • Leverage the run_openfast functionality to compile a turbsim binary

3.4.9. 09_distributed_aero

Tune a controller for distributed aerodynamic control In this example:

  • Read .yaml input file

  • Load an openfast turbine model

  • Read text file with rotor performance properties

  • Load blade information

  • Tune controller with flap actuator

Note

  • You will need a turbine model with DAC capabilites in order to run this. The curious user can contact Nikhar Abbas (nikhar.abbas@nrel.gov) for available models, if they do not have any themselves.

3.4.10. 10_linear_params

Load a turbine, tune a controller, export linear model In this example:

  • Load a turbine from OpenFAST

  • Tune a controller

  • Use tuning parameters to export linear model

3.4.11. 11_robust_tuning

Controller tuning to satisfy a robustness criteria

Note that this example necessitates the mbc3 through either pyFAST or WEIS pyFAST is the easiest to install by cloning https://github.com/OpenFAST/openfast_toolbox and running python setup.py develop from your conda environment

In this example:

  • setup ROSCO’s robust tuning methods for the IEA15MW on the UMaine Semi-sub

  • run a the standard tuning method to find k_float

  • run robust tuning to find omega_pc schedule satisfy a prescribed stability margin

  • Tune ROSCO’s pitch controller using omega_pc schedule

  • Plot gain schedule

The example is put in a function call to show the ability to load linear models in parallel

3.4.12. 12_tune_ipc

Load a turbine, tune a controller with IPC In this example:

  • Load a turbine from OpenFAST

  • Tune a controller with IPC

  • Run simple simulation with open loop control

3.4.13. 14_open_loop_control

Load a turbine, tune a controller with open loop control commands In this example:

  • Load a turbine from OpenFAST

  • Tune a controller

  • Write open loop inputs

  • Run simple simulation with open loop control

3.4.14. 15_pass_through

Use the runFAST scripts to set up an example, use pass through in yaml In this example:

  • use run_FAST_ROSCO class to set up a test case

3.4.15. 16_external_dll

Run openfast with ROSCO and external control interface IEA-15MW will call NREL-5MW controller and read control inputs

3.4.16. 17a_zeromq_simple

Run ROSCO using the ROSCO toolbox control interface and execute communication with ZeroMQ.

A demonstrator for ZeroMQ communication. Instead of using ROSCO with with control interface, one could call ROSCO from OpenFAST, and communicate with ZeroMQ through that. this_dir

3.4.17. 17b_zeromq_multi_openfast

Run multiple openfast simulations and execute communication with ZeroMQ.

3.4.18. 18_pitch_offsets

Run openfast with ROSCO and pitch offset faults Set up and run simulation with pitch offsets, check outputs

3.4.19. 19_update_discon_version

Test and demonstrate update_discon_version() function for converting an old ROSCO input to the current version

3.4.20. 20_active_wake_control

Run openfast with ROSCO and active wake control Set up and run simulation with AWC, check outputs Active wake control (AWC) with blade pitching is implemented in this example with two approaches as detailed below:

3.4.21. 21_optional_inputse_discon_version

Test and demonstrate update_discon_version() function for converting an old ROSCO input to the current version

3.4.22. 22_cable_control

Run openfast with ROSCO and cable control Set up and run simulation with pitch offsets, check outputs

ROSCO currently supports user-defined hooks for cable control actuation, if CC_Mode = 1. The control logic can be determined in Controllers.f90 with the CableControl subroutine. The CableControl subroutine takes an array of CC_DesiredL (length) equal to the ChannelIDs set in MoorDyn and determines the length and change in length needed for MoorDyn using a 2nd order actuator model (CC_ActTau). In the DISCON input, users must specify CC_GroupIndex relating to the deltaL of each control ChannelID. These indices can be found in the ServoDyn summary file (*SrvD.sum)

In the example below (and hard-coded in ROSCO) a step change of -10 m on line 1 is applied at 50 sec.

3.4.23. 23_structural_control

Run openfast with ROSCO and structural control Set up and run simulation with pitch offsets, check outputs

ROSCO currently supports user-defined hooks for structural control control actuation, if StC_Mode = 1. The control logic can be determined in Controllers.f90 with the StructrualControl subroutine. In the DISCON input, users must specify StC_GroupIndex relating to the control ChannelID. These indices can be found in the ServoDyn summary file (*SrvD.sum)

In the example below, we implement a smooth step change mimicing the exchange of ballast from the upwind column to the down wind columns

OpenFAST v3.5.0 is required to run this example

3.4.24. 24_floating_feedback

Run openfast with ROSCO and all the floating feedback methods Floating feedback methods available in ROSCO/ROSCO_Toolbox

  1. Automated tuning, constant for all wind speeds

  2. Automated tuning, varies with wind speed

  3. Direct tuning, constant for all wind speeds

  4. Direct tuning, varies with wind speeds

3.4.25. 25_rotor_position_control

Run ROSCO with rotor position control Run a steady simulation, use the azimuth output as an input to the next steady simulation, with different ICs

3.4.26. 26_marine_hydro

Run MHK turbine in OpenFAST with ROSCO torque controller

3.4.27. 27_power_ref_control

Run openfast with ROSCO and cable control Demonstrate a simulation with a generator reference speed that changes with estimated wind speed Set reference rotor speed as a function of wind speed (estimate in ROSCO)

3.4.28. 28_tower_resonance

Demonstrate tower resonance avoidance controller Set up and run simulation with tower resonance avoidance