def PowerCurveParametricExample1():
""" Example to run a set of FAST simulations to determine a power curve.
In this example, the WS, RPM and Pitch are set within a for loop.
If the controller and generator are active, these are just "initial conditions".
Additional parameters may be set by adjusting the BaseDict.
This script is based on a reference directory which contains a reference main input file (.fst)
Everything is copied to a working directory.
The different fast inputs are generated based on a list of dictionaries, named `PARAMS`.
For each dictionary:
- they keys are "path" to a input parameter, e.g. `EDFile|RotSpeed` or `TMax`.
These should correspond to whater name of the variable is used in the FAST inputs files.
- they values are the values corresponding to this parameter
"""
# --- Parameters for this script
FAST_EXE = os.path.join(MyDir, '../../../data/openfast.exe') # Location of a FAST exe (and dll)
ref_dir = os.path.join(MyDir, '../../../data/NREL5MW/') # Folder where the fast input files are located (will be copied)
main_file = 'Main_Onshore_OF2.fst' # Main file in ref_dir, used as a template
work_dir = '_NREL5MW_PowerCurveParametric/' # Output folder (will be created)
# --- Defining the parametric study (list of dictionnaries with keys as FAST parameters)
WS = [3,5,7,9 ,11,13,15]
RPM = [5,6,7,10,10,10,10] # initial conditions
PITCH = [0,0,0,0 ,5 ,10,15] # initial conditions
BaseDict = {'TMax': 100, 'DT': 0.01, 'DT_Out': 0.1}
#BaseDict = case_gen.paramsNoController(BaseDict)
#BaseDict = case_gen.paramsStiff(BaseDict)
#BaseDict = case_gen.paramsNoGen(BaseDict)
PARAMS=[]
for wsp,rpm,pitch in zip(WS,RPM,PITCH): # NOTE: same length of WS and RPM otherwise do multiple for loops
p=BaseDict.copy()
p['EDFile|RotSpeed'] = rpm
p['EDFile|BlPitch(1)'] = pitch
p['EDFile|BlPitch(2)'] = pitch
p['EDFile|BlPitch(3)'] = pitch
p['InflowFile|HWindSpeed'] = wsp
p['InflowFile|WindType'] = 1 # Setting steady wind
p['__name__'] = 'ws{:04.1f}'.format(p['InflowFile|HWindSpeed'])
PARAMS.append(p)
# --- Generating all files in a workdir
fastFiles=case_gen.templateReplace(PARAMS, ref_dir, work_dir, removeRefSubFiles=True, main_file=main_file)
print(fastFiles)
# --- Creating a batch script just in case
runner.writeBatch(os.path.join(work_dir,'_RUN_ALL.bat'), fastFiles,fastExe=FAST_EXE)
# --- Running the simulations
print('>>> Running {} simulations in {} ...'.format(len(fastFiles), work_dir))
runner.run_fastfiles(fastFiles, fastExe=FAST_EXE, parallel=True, showOutputs=False, nCores=2)
# --- Simple Postprocessing
outFiles = [os.path.splitext(f)[0]+'.outb' for f in fastFiles]
avg_results = postpro.averagePostPro(outFiles,avgMethod='constantwindow',avgParam=10, ColMap = {'WS_[m/s]':'Wind1VelX_[m/s]'},ColSort='WS_[m/s]')
print('>>> Average results:')
print(avg_results)
avg_results.to_csv('_PowerCurve1.csv',sep='\t',index=False)
def main():
# --- Main Parameters
ref_dir = os.path.join(
MyDir, '../../../data/NREL5MW/'
) # Folder where the fast input files are located (will be copied)
FAST_EXE = os.path.join(
MyDir,
'../../../data/openfast.exe') # Location of a FAST exe (and dll)
main_file = 'Main_Onshore_OF2.fst' # Main file in ref_dir, used as a template
work_dir = '_NREL5MW_ParametricExcel/' # Output folder (will be created)
parametricFile = 'ParametricExcel.xlsx' # Excel file containing set of parameters
# --- Reading Excel file, converting it to a list of dictionaries, and generate input files
dfs = io.excel_file.ExcelFile(parametricFile).toDataFrame()
df = dfs[list(dfs.keys())[0]]
PARAMS = df.to_dict('records')
print(df)
fastFiles = case_gen.templateReplace(PARAMS,
ref_dir,
outputDir=work_dir,
removeRefSubFiles=True,
removeAllowed=False,
main_file=main_file)
# --- Running fast simulations
print('>>> Running {} simulations in {} ...'.format(
len(fastFiles), work_dir))
runner.writeBatch(os.path.join(work_dir, '_RUN_ALL.bat'),
fastFiles,
fastExe=FAST_EXE)
runner.run_fastfiles(fastFiles,
showOutputs=False,
fastExe=FAST_EXE,
nCores=4)
# --- Postpro - Computing averages at the end of the simluation
print('>>> Postprocessing...')
outFiles = [os.path.splitext(f)[0] + '.outb' for f in fastFiles]
ColKeepStats = [
'RotSpeed_[rpm]', 'BldPitch1_[deg]', 'RtAeroCp_[-]', 'RtAeroCt_[-]',
'Wind1VelX_[m/s]'
]
result = postpro.averagePostPro(outFiles,
avgMethod='constantwindow',
avgParam=5,
ColKeep=ColKeepStats,
ColSort='RotSpeed_[rpm]')
result.to_csv('ParametricExcel_Summary.csv', sep='\t', index=False)
print('Average values saved to _ParametricExcel_Summary.csv')
def PowerCurveParametricExample2():
""" Example to run a set of FAST simulations to determine a power curve.
In this example, the WS, RPM and Pitch are set within a for loop.
If the controller and generator are active, these are just "initial conditions".
Additional parameters may be set by adjusting the BaseDict.
This script is based on a reference directory which contains a reference main input file (.fst)
Everything is copied to a working directory.
The different fast inputs are generated based on a list of dictionaries, named `PARAMS`.
For each dictionary:
- they keys are "path" to a input parameter, e.g. `EDFile|RotSpeed` or `TMax`.
These should correspond to whater name of the variable is used in the FAST inputs files.
- they values are the values corresponding to this parameter
"""
# --- Parameters for this script
FAST_EXE = os.path.join(MyDir, '../../../data/openfast.exe') # Location of a FAST exe (and dll)
ref_dir = os.path.join(MyDir, '../../../data/NREL5MW/') # Folder where the fast input files are located (will be copied)
main_file = 'Main_Onshore_OF2.fst' # Main file in ref_dir, used as a template
work_dir = '_NREL5MW_PowerCurveParametric2/' # Output folder (will be created)
out_Ext = '.outb' # Output extension
# --- Defining the parametric study (list of dictionnaries with keys as FAST parameters)
WS = [3,5,7,9 ,11,13,15]
RPM = [5,6,7,10,10,10,10]
PITCH = [0,0,0,0 ,5 ,10,15]
BaseDict = {'TMax': 10, 'DT': 0.01, 'DT_Out': 0.1}
PARAMS = case_gen.paramsWS_RPM_Pitch(WS, RPM, PITCH, baseDict=BaseDict, flatInputs=True)
# --- Generating all files in a workdir
fastFiles = case_gen.templateReplace(PARAMS, ref_dir, work_dir, removeRefSubFiles=True, removeAllowed=True, main_file=main_file)
# --- Creating a batch script just in case
runner.writeBatch(os.path.join(work_dir,'_RUN_ALL.bat'), fastFiles,fastExe=FAST_EXE)
# --- Running the simulations
runner.run_fastfiles(fastFiles, fastExe=FAST_EXE, parallel=True, showOutputs=False, nCores=2)
# --- Simple Postprocessing
outFiles = [os.path.splitext(f)[0]+out_Ext for f in fastFiles]
avg_results = postpro.averagePostPro(outFiles,avgMethod='constantwindow',avgParam=10, ColMap = {'WS_[m/s]':'Wind1VelX_[m/s]'},ColSort='WS_[m/s]')
print('>>> Average results:')
print(avg_results)
avg_results.to_csv('_PowerCurve2.csv',sep='\t',index=False)
def ParametricExample():
""" Example to run a set of OpenFAST simulations (parametric study)
This script uses a reference directory (`ref_dir`) which contains a reference input file (.fst)
1) The reference directory is copied to a working directory (`out_dir`).
2) All the fast input files are generated in this directory based on a list of dictionaries (`PARAMS`).
For each dictionary in this list:
- The keys are "path" to a input parameter, e.g. `EDFile|RotSpeed` or `FAST|TMax`.
These should correspond to the variables used in the FAST inputs files.
- The values are the values corresponding to this parameter
For instance:
PARAMS[0]['DT'] = 0.01
PARAMS[0]['EDFile|RotSpeed'] = 5
PARAMS[0]['InflowFile|HWindSpeed'] = 10
3) The simulations are run, successively distributed on `nCores` CPUs.
4) The output files are read, and averaged based on a method (e.g. average over a set of periods,
see averagePostPro in postpro for the different averaging methods).
A pandas DataFrame is returned
"""
# --- Parameters for this script
ref_dir = 'NREL5MW/' # Folder where the fast input files are located (will be copied)
out_dir = 'NREL5MW_Parametric/' # Output folder (will be created)
main_file = 'Main_Onshore_OF2.fst' # Main file in ref_dir, used as a template
FAST_EXE = 'openfast2.3_x64s.exe' # Location of a FAST exe (and dll)
# --- Defining the parametric study (list of dictionnaries with keys as FAST parameters)
WS = [3, 5, 6, 7]
RPM = [10, 12, 13, 15]
BaseDict = {'TMax': 10, 'DT': 0.01, 'DT_Out': 0.1}
BaseDict = case_gen.paramsNoController(BaseDict) # Remove the controller
#BaseDict = case_gen.paramsControllerDLL(BaseDict) # Activate the controller
#BaseDict = case_gen.paramsStiff(BaseDict) # Make the turbine stiff (except generator)
#BaseDict = case_gen.paramsNoGen(BaseDict) # Remove the Generator DOF
PARAMS = []
for i, (wsp, rpm) in enumerate(
zip(WS, RPM)
): # NOTE: same length of WS and RPM otherwise do multiple for loops
p = BaseDict.copy()
#p['AeroFile|TwrAero'] = True
#p['EDFile|BldFile(1)|AdjBlMs'] =1.1
#p['EDFile|BldFile(2)|AdjBlMs'] =1.1
#p['EDFile|BldFile(3)|AdjBlMs'] =1.1
p['EDFile|RotSpeed'] = rpm
p['InflowFile|HWindSpeed'] = wsp
p['InflowFile|WindType'] = 1 # Setting steady wind
p['__name__'] = '{:03d}_ws{:04.1f}_om{:04.2f}'.format(
i, p['InflowFile|HWindSpeed'], p['EDFile|RotSpeed'])
PARAMS.append(p)
i = i + 1
# --- Generating all files in a output directory
fastfiles = case_gen.templateReplace(PARAMS,
ref_dir,
outputDir=out_dir,
removeRefSubFiles=True,
main_file=main_file,
oneSimPerDir=False)
print(fastfiles)
# --- Creating a batch script just in case
runner.writeBatch(os.path.join(out_dir, '_RUN_ALL.bat'),
fastfiles,
fastExe=FAST_EXE)
# --- Running the simulations
runner.run_fastfiles(fastfiles,
fastExe=FAST_EXE,
parallel=True,
showOutputs=False,
nCores=4)
# --- Simple Postprocessing
# (averaging each signal over the last period for each simulation)
outFiles = [os.path.splitext(f)[0] + '.outb' for f in fastfiles]
avg_results = postpro.averagePostPro(
outFiles,
avgMethod='periods',
avgParam=1,
ColMap={'WS_[m/s]': 'Wind1VelX_[m/s]'},
ColSort='WS_[m/s]')
avg_results.drop('Time_[s]', axis=1, inplace=True)
print(avg_results)
return avg_results