More oneROSCO2 updates, primarily housekeeping

Examples/example_12.py

@@ -21,32 +21,28 @@
 from ROSCO_toolbox import turbine as ROSCO_turbine
 from ROSCO_toolbox import controller as ROSCO_controller
 
+
 def run_example():
     # Shorthand directories
     this_dir = os.path.dirname(os.path.abspath(__file__))
     tune_dir = os.path.join(this_dir, '../Tune_Cases')
     test_dir = os.path.join(this_dir, '../Test_Cases')
 
-    # Setup linear turbine paths
-    linfile_root = os.path.join(test_dir, 'IEA-15-240-RWT-UMaineSemi', 'linearizations')
-    load_parallel = True
-    linturb_options = {'linfile_root': linfile_root,
-                        'load_parallel': load_parallel}
-
     # ROSCO options
-    parameter_filename = os.path.join(tune_dir, 'IEA15MW.yaml')
+    parameter_filename = os.path.join(tune_dir, 'IEA15MW_robust.yaml')
     inps = load_rosco_yaml(parameter_filename)
     path_params = inps['path_params']
     turbine_params = inps['turbine_params']
     controller_params = inps['controller_params']
+    linmodel_tuning = inps['linmodel_tuning']
     ROSCO_options = {
         'path_params': path_params,
         'turbine_params': turbine_params,
         'controller_params': controller_params
     }
 
     # Path options
-    example_out_dir = os.path.join( os.path.dirname(os.path.abspath(__file__)), 'examples_out' )
+    example_out_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'examples_out')
     output_name = '12_robust_scheduling'
     path_options = {'output_dir': example_out_dir,
                     'output_name': output_name
@@ -65,31 +61,31 @@ def run_example():
     k_float = controller.Kp_float
 
     # Scheduling options
-    opt_options = { 'driver': 'optimization', #'design_of_experiments',
-                    'windspeed': [12, 13, 14, 15, 18, 24],
-                    'stability_margin': 0.1,
-                    'omega':[0.05, 0.2], # two inputs denotes a range for a design variable
-                    'k_float': [k_float]}    # one input denotes a set value
+    opt_options = {'driver': 'optimization',  # 'design_of_experiments',
+                   'windspeed': controller_params['U_pc'],
+                   'stability_margin': linmodel_tuning['stability_margin'],
+                   'omega': [linmodel_tuning['omega_pc']['min'],
+                             linmodel_tuning['omega_pc']['max']],  # two inputs denotes a range for a design variable
+                   'k_float': [k_float]}    # one input denotes a set value
 
     # Collect options
     options = {}
-    options['linturb_options'] = linturb_options
-    options['ROSCO_options']   = ROSCO_options
-    options['path_options']    = path_options
-    options['opt_options']     = opt_options
+    options['linturb_options'] = linmodel_tuning
+    options['ROSCO_options'] = ROSCO_options
+    options['path_options'] = path_options
+    options['opt_options'] = opt_options
 
     # Run robust scheduling
     sd = rsched_driver(options)
     sd.setup()
     sd.execute()
 
     # Re-define ROSCO tuning parameters
-    controller.U_pc = opt_options['windspeed']
     controller.omega_pc = sd.omegas
     controller.zeta_pc = np.ones(
         len(opt_options['windspeed'])) * controller.zeta_pc
 
-    # Tune ROSCO with to satisfy robust stability margin 
+    # Tune ROSCO with to satisfy robust stability margin
     controller.tune_controller(turbine)
 
     # Plot gain schedule
@@ -118,10 +114,10 @@ def run_example():
     ax[4].set_ylabel('Integral Gain')
     ax[4].grid()
 
-
-    if False:
+    if True:
         plt.show()
     else:
         plt.savefig(os.path.join(example_out_dir, '12_RobustSched.png'))
+
 if __name__ == '__main__':
     run_example()

README.md

@@ -1,23 +1,31 @@
 # NREL's Reference OpenSource Controller (ROSCO) toolbox for wind turbine applications
-NREL's Reference OpenSource Controller (ROSCO) toolbox for wind turbine applications is a toolbox designed to ease controller implementation for the wind turbine researcher. Some primary capabilities include:
+NREL's Reference OpenSource Controller (ROSCO) for wind turbine applications is a toolset designed to ease controller use and implementation for the wind turbine researcher. Some primary capabilities include:
+* A reference controller with industry-standard functionality 
 * Generic tuning of NREL's ROSCO controller
 * Simple 1-DOF turbine simulations for quick controller capability verifications
 * Parsing of OpenFAST input and output files
 
 
 ## Introduction
-The NREL Reference OpenSource Controller (ROSCO) provides an open, modular and fully adaptable baseline wind turbine controller to the scientific community. The ROSCO toolbox leverages this architecture and implementation to provide a generic tuning process for the controller. Because of the open character and modular set-up, scientists are able to collaborate and contribute in making continuous improvements to the code for the controller and the toolbox. The ROSCO toolbox is a mostly-python code base with a number of functionalities.
+The NREL Reference OpenSource Controller (ROSCO) provides an open, modular and fully adaptable baseline wind turbine controller to the scientific community. The ROSCO toolbox leverages this architecture and implementation to provide a generic tuning process for the controller. Because of the open character and modular set-up, scientists are able to collaborate and contribute in making continuous improvements to the code for the controller and the toolbox. The ROSCO controller is implemented in FORTRAN, while the remainder of the toolset is a mostly-python code base with a number of functionalities.
 
-* [ROSCO](https://github.com/NREL/ROSCO) - the fortran source code for the ROSCO controller. 
-* [Examples](https://github.com/NREL/ROSCO_toolbox/tree/master/examples) - short working examples of the capabilities of the ROSCO toolbox. 
-* [Tune_Cases](https://github.com/NREL/ROSCO_toolbox/tree/master/Tune_Cases) - example generic tuning scripts for a number of open-source reference turbines.
-* [Test_Cases](https://github.com/NREL/ROSCO_toolbox/tree/master/Test_Cases) - numerous NREL 5MW bases cases to run for controller updates and comparisons. A "test-suite", if you will...
-* [Matlab_Toolbox](https://github.com/NREL/ROSCO_toolbox/tree/master/Matlab_Toolbox) - MATLAB scripts to parse and plot simulation output data.
-* [ofTools](https://github.com/NREL/ROSCO_toolbox/tree/master/ofTools) - A number of scripts to facilitate usage of OpenFAST and manage OpenFAST input and output files. 
+* [ROSCO](https://github.com/NREL/ROSCO/tree/main/ROSCO) - the fortran source code for the ROSCO controller. 
+* [Examples](https://github.com/NREL/ROSCO/tree/main/Examples) - short working examples of the capabilities of the ROSCO toolbox. 
+* [Tune_Cases](https://github.com/NREL/ROSCO/tree/main/Tune_Cases) - example generic tuning scripts for a number of open-source reference turbines.
+* [Test_Cases](https://github.com/NREL/ROSCO/tree/main/Test_Cases) - numerous NREL 5MW bases cases to run for controller updates and comparisons. A "test-suite", if you will...
+* [Matlab_Toolbox](https://github.com/NREL/ROSCO/tree/main/Matlab_Toolbox) - MATLAB scripts to parse and plot simulation output data.
+* [ofTools](https://github.com/NREL/ROSCO/tree/main/ROSCO_toolbox/ofTools) - A number of scripts to facilitate usage of OpenFAST and manage OpenFAST input and output files. 
+* [linear](https://github.com/NREL/ROSCO/tree/main/ROSCO_toolbox/linear) - Scripts to aid with the use of linear models for controller tuning and simplified simulation. 
 
 
 ## Documentation
-All relevant documentation about the ROSCO toolbox and ROSCO controller can be found at through [ROSCO's readthedocs webpage](https://rosco-toolbox.readthedocs.io/en/latest/). Here, users can find the information on [installing the ROSCO toolbox](https://rosco-toolbox.readthedocs.io/en/latest/source/install.html#installing-the-rosco-toolbox) and [compiling ROSCO](https://rosco-toolbox.readthedocs.io/en/latest/source/install.html#compiling-rosco) for control purposes. Additionally, there is information on the standard workflow and uses cases for the ROSCO toolchain, and more. 
+All relevant documentation about the ROSCO toolbox and ROSCO controller can be found at through [ROSCO's readthedocs webpage](https://rosco.readthedocs.io/en/latest/). Here, users can find the information on [installing the ROSCO tools](https://rosco.readthedocs.io/en/latest/source/install.html) and [compiling ROSCO](https://rosco.readthedocs.io/en/latest/source/install.html#rosco-controller) for control purposes. Additionally, there is information on the standard workflow, uses cases for the ROSCO tool-chain, and more. 
+
+## Issues and Discussion
+If you find issues with any of the code that resides in this repository, it is encouraged for you to open a [GitHub issue](https://github.com/NREL/ROSCO/issues). If you have general questions or comments regarding the code, please start a [discussion via GitHub](https://github.com/NREL/ROSCO/discussions). We encourage you to use these resources for all ROSCO-related questions and comments, rather than other resources such as the FAST forums. This helps us keep ROSCO-related items centralized, and provides a singular place for the community to look when they have questions that might arise. Please keep in mind that we will do our very best to respond in a timely manner, but may take a few days to get back to you if you catch us during a busy time. 
+
+## Contributing
+If it wasn't obvious from _open-source_ being in the title of the tool-set, this is an open-source code base that we would love for the community to contribute to. If you find yourself fixing any bugs, writing new routines, or even making small typo changes, please submit a [pull request](https://github.com/NREL/ROSCO/pulls). 
 
 ## Survey
 Please help us better understand the ROSCO user-base and how we can improve rosco through this brief survey:
@@ -27,18 +35,18 @@ Please help us better understand the ROSCO user-base and how we can improve rosc
 If the ROSCO Toolbox played a role in your research, please cite it. This software can be
 cited as:
 
-   NREL: ROSCO Toolbox. Version 2.3.0, https://github.com/NREL/rosco_toolbox, 2021.
+   NREL: ROSCO. Version 2.4.0, https://github.com/NREL/ROSCO, 2021.
 
 For LaTeX users:
 
 ```
 @misc{ROSCO_toolbox_2021,
     author = {NREL},
-    title = {{ROSCO Toolbox. Version 2.3.0}},
+    title = {{ROSCO. Version 2.4.0}},
     year = {2021},
     publisher = {GitHub},
     journal = {GitHub repository},
-    url = {https://github.com/NREL/rosco_toolbox}
+    url = {https://github.com/NREL/ROSCO}
     }
 ```
 If the ROSCO generic tuning theory and implementation played a roll in your research, please cite the following paper
@@ -54,10 +62,6 @@ URL = {https://wes.copernicus.org/preprints/wes-2021-19/},
 DOI = {10.5194/wes-2021-19}
 }
 ```
-Additionally, if you have extensively used the [ROSCO](https://github.com/NREL/ROSCO) controller or [WISDEM](https://github.com/wisdem/wisdem), please cite them accordingly. 
-
 
 ## Additional Contributors and Acknowledgments
-Primary contributions to the ROSCO Toolbox have been provided by researchers the National Renewable Energy Laboratory (Nikhar J. Abbas, Daniel Zalkind, Alan Wright, and Paul Fleming) and the University of Colorado Boulder (Lucy Pao). Much of the intellect behind these contributions has been inspired or derived from an extensive amount of work in the literature. The bulk of this has been cited through the primary publications about this work. 
-
-There have been a number of contributors to the logic of the ROSCO controller itself. Please see the [ROSCO github page](https://github.com/NREL/ROSCO) for more information on who these contributors have been. 
+Primary contributions to ROSCO have been provided by researchers the National Renewable Energy Laboratory and the University of Colorado Boulder. Additionally, the ROSCO controller was built upon the foundations of the [Delft Research Controller](https://github.com/TUDelft-DataDrivenControl/DRC_Fortran). Much of the intellect behind these contributions has been inspired or derived from an extensive amount of work in the literature. The bulk of this has been cited through the primary publications about this work. 

ROSCO/CMakeLists.txt

@@ -1,5 +1,5 @@
 cmake_minimum_required(VERSION 3.6)
-project(ROSCO VERSION 2.3.0 LANGUAGES Fortran)
+project(ROSCO VERSION 2.4.0 LANGUAGES Fortran)
 
 set(CMAKE_Fortran_MODULE_DIRECTORY "${CMAKE_BINARY_DIR}/ftnmods")
 

ROSCO/src/Constants.f90

@@ -10,7 +10,7 @@
 ! specific language governing permissions and limitations under the License.
 
 MODULE Constants
-    Character(*), PARAMETER     :: rosco_version = 'v2.3.0'             ! ROSCO version
+    Character(*), PARAMETER     :: rosco_version = 'v2.4.0'             ! ROSCO version
     REAL(8), PARAMETER          :: RPS2RPM = 9.5492966                  ! Factor to convert radians per second to revolutions per minute.
     REAL(8), PARAMETER          :: R2D = 57.295780                      ! Factor to convert radians to degrees.
     REAL(8), PARAMETER          :: D2R = 0.0175                         ! Factor to convert degrees to radians.

ROSCO_toolbox/__init__.py

@@ -3,4 +3,4 @@
 
 __author__ = """Nikhar J. Abbas and Daniel S. Zalkind"""
 __email__ = 'nikhar.abbas@nrel.gov'
-__version__ = '2.3.0'
+__version__ = '2.4.0'

ROSCO_toolbox/controller.py

@@ -13,6 +13,7 @@
 import sys
 import datetime
 from scipy import interpolate, gradient, integrate
+from ROSCO_toolbox.utilities import list_check
 
 # Some useful constants
 now = datetime.datetime.now()
@@ -63,11 +64,12 @@ def __init__(self, controller_params):
         self.Flp_Mode           = controller_params['Flp_Mode']
 
         # Necessary parameters
-        self.U_pc               = controller_params['U_pc']
-        self.zeta_pc            = controller_params['zeta_pc']
-        self.omega_pc           = controller_params['omega_pc']
-        self.zeta_vs            = controller_params['zeta_vs']
-        self.omega_vs           = controller_params['omega_vs']
+        self.U_pc = list_check(controller_params['U_pc'], return_bool=False)
+        self.zeta_pc = list_check(controller_params['zeta_pc'], return_bool=False)
+        self.omega_pc = list_check(controller_params['omega_pc'], return_bool=False)
+        self.zeta_vs = controller_params['zeta_vs']
+        self.omega_vs = controller_params['omega_vs']
+        self.interp_type = controller_params['interp_type']
 
         # Optional parameters with defaults
         self.min_pitch          = controller_params['min_pitch']
@@ -122,6 +124,12 @@ def __init__(self, controller_params):
         if self.WS_GS_n <= self.PC_GS_n:
             raise Exception('Number of WS breakpoints is not greater than pitch control breakpoints')
 
+        # Error checking: pitch controller inputs
+        if list_check(self.U_pc) and \
+            (list_check(self.omega_pc) or list_check(self.zeta_pc)) and \
+                not len(self.U_pc) == len(self.omega_pc) == len(self.zeta_pc):
+            raise Exception(
+                'U_pc, omega_pc, and zeta_pc are all list-like and are not of equal length')
 
 
     def tune_controller(self, turbine):
@@ -241,17 +249,18 @@ def tune_controller(self, turbine):
         B_tau = B_tau * np.ones(len(v))
 
         # Resample omega_ and zeta_pc at above rated wind speeds
-        if self.U_pc \
-            and isinstance(self.omega_pc, (list,np.ndarray)) \
-            and isinstance(self.zeta_pc, (list,np.ndarray)) \
-            and len(self.U_pc) == len(self.omega_pc) == len(self.zeta_pc):
-            self.omega_pc_U = multi_sigma(v_above_rated[1:],self.U_pc,self.omega_pc)
-            self.zeta_pc_U  = multi_sigma(v_above_rated[1:],self.U_pc,self.zeta_pc)
-        elif isinstance(self.omega_pc, float) and isinstance(self.zeta_pc, float):
+        if not list_check(self.omega_pc) and not list_check(self.zeta_pc):
             self.omega_pc_U = self.omega_pc * np.ones(len(v_above_rated[1:]))
             self.zeta_pc_U = self.zeta_pc * np.ones(len(v_above_rated[1:]))
         else:
-            raise Exception('ROSCO_toolbox: The lengths of U_pc, omega_pc, and zeta_pc must be equal')
+            if self.interp_type == 'sigma':  # sigma interpolation
+                self.omega_pc_U = multi_sigma(v_above_rated[1:], self.U_pc, self.omega_pc)
+                self.zeta_pc_U = multi_sigma(v_above_rated[1:], self.U_pc, self.zeta_pc)
+            else:   # standard scipy interpolation types
+                interp_omega = interpolate.interp1d(self.U_pc, self.omega_pc, kind=self.interp_type, bounds_error=False, fill_value='extrapolate')
+                interp_zeta = interpolate.interp1d(self.U_pc, self.zeta_pc, kind=self.interp_type, bounds_error=False, fill_value='extrapolate')
+                self.omega_pc_U = interp_omega(v_above_rated[1:])
+                self.zeta_pc_U = interp_zeta(v_above_rated[1:])
 
         # -- Find gain schedule --
         self.pc_gain_schedule = ControllerTypes()

ROSCO_toolbox/inputs/toolbox_schema.yaml

@@ -123,7 +123,7 @@ properties:
                 minimum: 0
                 maximum: 3
                 default: 2
-                description: Generator torque control mode in above rated conditions (0- constant torque, 1- constant power, 2- TSR tracking PI control, 3- TSR tracking and constant power)
+                description: Generator torque control mode in above rated conditions (0- constant torque, 1- constant power, 2- TSR tracking PI control with constant torque, 3- TSR tracking with constant power)
             PC_ControlMode:     
                 type: number
                 minimum: 0
@@ -203,6 +203,11 @@ properties:
                     type: number
                     minimum: 0
                 default: [0.2]
+            interp_type:
+                type: string
+                description: Type of interpolation between above rated tuning values (only used for multiple pitch controller tuning values)
+                default: linear
+                enum: ['sigma', 'linear', 'quadratic', 'cubic']
             zeta_vs:                        
                 type: number
                 minimum: 0
@@ -305,7 +310,7 @@ properties:
                 minimum: 0
                 description: Flap controller desired natural frequency [rad/s]
                 unit: rad/s
-            
+
     filter_params:
         type: object
         default: {}
@@ -323,8 +328,42 @@ properties:
                 default: 0.01042
                 description: Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]
 
-    # modeling_options:
-    #     type: object
-    #     default: {}
-    #     properties:
-
+    linmodel_tuning:
+        type: object
+        default: {}
+        description: Inputs used for tuning ROSCO using linear (level 2) models
+        properties:
+            type: 
+                type: string
+                description: Type of level 2 based tuning - robust gain scheduling (robust) or simulation based optimization (simulation)
+                default: 'none' 
+                enum: ['none', 'robust', 'simulation']
+            linfile_path:
+                type: string
+                description: Path to OpenFAST linearization (.lin) files, if they exist 
+                default: none
+            lintune_outpath:
+                type: string
+                description: Path for outputs from linear model based tuning
+                default: lintune_outfiles
+            load_parallel:
+                type: boolean
+                description: Load linearization files in parallel (True/False)
+                default: False
+            stability_margin:
+                type: [number, array]
+                description: Desired maximum stability margin
+                default: 0.1
+            omega_pc:
+                type: object
+                default: {}
+                description: Pitch controller bandwidth constraints
+                min:
+                    type: [number, array]
+                    default: 0.0
+                    description: Desired maximum allowable omega for robust tuning. Array must be of length U_pc.
+                max:
+                    type: [number, array]
+                    default: 0.2
+                    description: Desired maximum allowable omega for robust tuning. Array must be of length U_pc.
+