def run_problem(optFlag=False, prob_ref=None):
# Initialize blade design
refBlade = ReferenceBlade()
if rank == 0:
refBlade.verbose = True
else:
refBlade.verbose = False
refBlade.NINPUT = 8
Nsection_Tow = 19
refBlade.NPTS = 30
refBlade.spar_var = ['Spar_cap_ss', 'Spar_cap_ps'] # SS, then PS
refBlade.te_var = 'TE_reinforcement'
refBlade.le_var = 'le_reinf'
refBlade.validate = False
refBlade.fname_schema = fname_schema
blade = refBlade.initialize(fname_input)
Analysis_Level = 0
FASTpref = {}
FASTpref['Analysis_Level'] = Analysis_Level
fst_vt = {}
# Initialize and execute OpenMDAO problem with input data
if MPI:
num_par_fd = MPI.COMM_WORLD.Get_size()
prob = om.Problem(model=om.Group(num_par_fd=num_par_fd))
prob.model.approx_totals(method='fd')
prob.model.add_subsystem('comp',
Optimize_MonopileTurbine(
RefBlade=blade,
Nsection_Tow=Nsection_Tow,
folder_output=folder_output),
promotes=['*'])
else:
prob = om.Problem()
prob.model = Optimize_MonopileTurbine(RefBlade=blade,
Nsection_Tow=Nsection_Tow,
folder_output=folder_output)
prob.model.nonlinear_solver = om.NonlinearRunOnce()
prob.model.linear_solver = om.DirectSolver()
if optFlag and not prob_ref is None:
if MPI:
num_par_fd = MPI.COMM_WORLD.Get_size()
prob = om.Problem(model=om.Group(num_par_fd=num_par_fd))
prob.model.approx_totals(method='fd')
prob.model.add_subsystem('comp',
Optimize_MonopileTurbine(
RefBlade=blade,
Nsection_Tow=Nsection_Tow,
folder_output=folder_output),
promotes=['*'])
else:
prob = om.Problem()
prob.model = Optimize_MonopileTurbine(RefBlade=blade,
Nsection_Tow=Nsection_Tow,
folder_output=folder_output)
# --- Driver ---
prob.driver = om.pyOptSparseDriver()
prob.driver.options['optimizer'] = 'CONMIN'
prob.driver.opt_settings['ITMAX'] = 15
prob.driver.opt_settings['IPRINT'] = 4
# ----------------------
# --- Objective ---
# prob.model.add_objective('lcoe')
prob.model.add_objective('AEP', scaler=-1.)
#prob.model.add_objective('mass_one_blade')
# ----------------------
# --- Design Variables ---
indices_no_root = range(2, refBlade.NINPUT)
indices_no_root_no_tip = range(2, refBlade.NINPUT - 1)
indices_no_max_chord = range(3, refBlade.NINPUT)
prob.model.add_design_var('sparT_in',
indices=indices_no_root_no_tip,
lower=0.001,
upper=0.200)
prob.model.add_design_var('chord_in',
indices=indices_no_max_chord,
lower=0.5,
upper=7.0)
prob.model.add_design_var('theta_in',
indices=indices_no_root,
lower=-7.5,
upper=20.0)
prob.model.add_design_var('teT_in',
lower=prob_ref['teT_in'] * 0.5,
upper=0.1)
#prob.model.add_design_var('leT_in', lower=prob_ref['leT_in']*0.5, upper=0.1)
# ----------------------
# --- Constraints ---
prob.model.add_subsystem('freq_check',
blade_freq_check(),
promotes=['freq_check_out'])
prob.model.connect('freq_curvefem',
'freq_check.freq_curvefem') #, src_indices=[0])
# Rotor
prob.model.add_constraint('tip_deflection_ratio', upper=1.0)
# prob.model.add_constraint('no_stall_constraint', upper=1.0)
prob.model.add_constraint('freq_check_out', lower=1.1)
#prob.model.add_constraint('rated_Q', lower=21.4e6, upper=21.6e6)
# prob.model.add_constraint('mass_one_blade', upper=prob_ref['mass_one_blade']*1.02)
prob.model.add_constraint('AEP', lower=0.99 * prob_ref['AEP'])
# ----------------------
# --- Recorder ---
filename_opt_log = folder_output + 'log_opt_' + blade['config']['name']
prob.driver.add_recorder(om.SqliteRecorder(filename_opt_log))
prob.driver.recording_options['includes'] = [
'AEP', 'total_blade_cost', 'lcoe', 'tip_deflection_ratio',
'mass_one_blade', 'theta_in'
]
prob.driver.recording_options['record_objectives'] = True
prob.driver.recording_options['record_constraints'] = True
prob.driver.recording_options['record_desvars'] = True
# ----------------------
# Initialize variable inputs
prob = initialize_variables(prob, blade, Analysis_Level, fst_vt)
# Run initial condition no matter what
print('Running at Initial Position:')
prob.run_model()
print('########################################')
print('')
print('Control variables')
print('Rotor diam: {:8.3f} m'.format(prob['diameter'][0]))
print('TSR: {:8.3f} -'.format(prob['control_tsr'][0]))
print('Rated vel: {:8.3f} m/s'.format(prob['rated_V'][0]))
print('Rated rpm: {:8.3f} rpm'.format(prob['rated_Omega'][0]))
print('Rated pitch: {:8.3f} deg'.format(prob['rated_pitch'][0]))
print('Rated thrust: {:8.3f} N'.format(prob['rated_T'][0]))
print('Rated torque: {:8.3f} N-m'.format(prob['rated_Q'][0]))
print('')
print('Constraints')
print('Max TD: {:8.3f} m'.format(prob['tip_deflection'][0]))
print('TD ratio: {:8.3f} -'.format(prob['tip_deflection_ratio'][0]))
print('Blade root M: {:8.3f} N-m'.format(prob['root_bending_moment'][0]))
print('')
print('Objectives')
print('AEP: {:8.3f} GWh'.format(prob['AEP'][0]))
print('LCoE: {:8.4f} $/MWh'.format(prob['lcoe'][0]))
print('')
print('Blades')
print('Blade mass: {:8.3f} kg'.format(prob['mass_one_blade'][0]))
print('Blade cost: {:8.3f} $'.format(prob['total_blade_cost'][0]))
print('Blade freq: {:8.3f} Hz'.format(prob['freq_curvefem'][0]))
print('3 blade M_of_I: ', prob['I_all_blades'], ' kg-m^2')
print('Hub M: ', prob['Mxyz_total'], ' kg-m^2')
print('')
print('RNA Summary')
print('RNA mass: {:8.3f} kg'.format(prob['tow.pre.mass'][0]))
print('RNA C_of_G (TT): ', prob['rna_cg'], ' m')
print('RNA M_of_I: ', prob['tow.pre.mI'], ' kg-m^2')
print('')
print('Tower')
print('Tower top F: ', prob['tow.pre.rna_F'], ' N')
print('Tower top M: ', prob['tow.pre.rna_M'], ' N-m')
print('Tower freqs: ', prob['tow.post.structural_frequencies'], ' Hz')
print('Tower vel: {:8.3f} kg'.format(prob['tow.wind.Uref'][0]))
print('Tower mass: {:8.3f} kg'.format(prob['tower_mass'][0]))
print('Tower cost: {:8.3f} $'.format(prob['tower_cost'][0]))
print('########################################')
# Angle of attack and stall angle
faoa, axaoa = plt.subplots(1, 1, figsize=(5.3, 4))
axaoa.plot(prob['r'],
prob['nostallconstraint.aoa_along_span'],
label='Initial aoa')
axaoa.plot(prob['r'],
prob['nostallconstraint.stall_angle_along_span'],
'.',
label='Initial stall')
axaoa.legend(fontsize=12)
plt.xlabel('Blade Span [m]', fontsize=14, fontweight='bold')
plt.ylabel('Angle [deg]', fontsize=14, fontweight='bold')
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
plt.grid(color=[0.8, 0.8, 0.8], linestyle='--')
plt.subplots_adjust(bottom=0.15, left=0.15)
fig_name = 'aoa.png'
faoa.savefig(folder_output + fig_name)
# Complete data dump
#prob.model.list_inputs(units=True)
#prob.model.list_outputs(units=True)
if optFlag:
if rank == 0:
print('Running Optimization:')
print('N design var: ',
2 * len(indices_no_root_no_tip) + len(indices_no_root) + 1)
if not MPI:
prob.model.approx_totals()
prob.run_driver()
if rank == 0:
# --- Save output .yaml ---
refBlade.write_ontology(fname_output, prob['blade_out'],
refBlade.wt_ref)
# --- Outputs plotting ---
print('AEP: \t\t\t %f\t%f GWh \t Difference: %f %%' %
(prob_ref['AEP'] * 1e-6, prob['AEP'] * 1e-6,
(prob['AEP'] - prob_ref['AEP']) / prob_ref['AEP'] * 100.))
print(
'LCoE: \t\t\t %f\t%f USD/MWh \t Difference: %f %%' %
(prob_ref['lcoe'] * 1.e003, prob['lcoe'] * 1.e003,
(prob['lcoe'] - prob_ref['lcoe']) / prob_ref['lcoe'] * 100.))
print('Blade cost: \t\t\t %f\t%f USD \t Difference: %f %%' %
(prob_ref['total_blade_cost'], prob['total_blade_cost'],
(prob['total_blade_cost'] - prob_ref['total_blade_cost']) /
prob_ref['total_blade_cost'] * 100.))
print('Blade mass: \t\t\t %f\t%f kg \t Difference: %f %%' %
(prob_ref['total_blade_mass'], prob['total_blade_mass'],
(prob['total_blade_mass'] - prob_ref['total_blade_mass']) /
prob_ref['total_blade_mass'] * 100.))
print('Tower cost: \t\t\t %f\t%f USD \t Difference: %f %%' %
(prob_ref['tower_cost'], prob['tower_cost'],
(prob['tower_cost'] - prob_ref['tower_cost']) /
prob_ref['tower_cost'] * 100.))
print('Tower mass: \t\t\t %f\t%f kg \t Difference: %f %%' %
(prob_ref['tower_mass'], prob['tower_mass'],
(prob['tower_mass'] - prob_ref['tower_mass']) /
prob_ref['tower_mass'] * 100.))
# ----------------------
# Theta
ft, axt = plt.subplots(1, 1, figsize=(5.3, 4))
axt.plot(prob_ref['r'], prob_ref['theta'], label='Initial')
axt.plot(prob_ref['r_in'], prob_ref['theta_in'], '.')
axt.plot(prob['r'], prob['theta'], label='Optimized')
axt.plot(prob['r_in'], prob['theta_in'], '.')
axt.legend(fontsize=12)
plt.xlabel('Blade Span [m]', fontsize=14, fontweight='bold')
plt.ylabel('Twist [deg]', fontsize=14, fontweight='bold')
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
plt.grid(color=[0.8, 0.8, 0.8], linestyle='--')
plt.subplots_adjust(bottom=0.15, left=0.15)
fig_name = 'theta.png'
ft.savefig(folder_output + fig_name)
# Angle of attack and stall angle
faoa, axaoa = plt.subplots(1, 1, figsize=(5.3, 4))
axaoa.plot(prob_ref['r'],
prob_ref['nostallconstraint.aoa_along_span'],
label='Initial aoa')
axaoa.plot(prob_ref['r'],
prob_ref['nostallconstraint.stall_angle_along_span'],
'.',
label='Initial stall')
axaoa.plot(prob['r'],
prob['nostallconstraint.aoa_along_span'],
label='Optimized aoa')
axaoa.plot(prob['r'],
prob['nostallconstraint.stall_angle_along_span'],
'.',
label='Optimized stall')
axaoa.legend(fontsize=12)
plt.xlabel('Blade Span [m]', fontsize=14, fontweight='bold')
plt.ylabel('Angle [deg]', fontsize=14, fontweight='bold')
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
plt.grid(color=[0.8, 0.8, 0.8], linestyle='--')
plt.subplots_adjust(bottom=0.15, left=0.15)
fig_name = 'aoa.png'
ft.savefig(folder_output + fig_name)
plt.show()
return prob, blade
rotor = Init_RotorSE_wRefBlade(rotor,
blade,
Analysis_Level=Analysis_Level,
fst_vt=fst_vt)
# rotor['chord_in'] = np.array([3.542, 3.54451799, 2.42342374, 2.44521374, 4.69032208, 6.3306303, 4.41245811, 1.419])
# rotor['theta_in'] = np.array([13.30800018, 13.30800018, 0.92624531, 10.41054813, 11.48955724, -0.60858835, -1.41595352, 4.89747605])
# rotor['sparT_in'] = np.array([0.00047, 0.00059925, 0.07363709, 0.13907431, 0.19551095, 0.03357394, 0.12021584, 0.00047])
# rotor['r_in'] = np.array([0., 0.02565783, 0.23892874, 0.39114299, 0.54335725, 0.6955715, 0.84778575, 1.])
# === run and outputs ===
tt = time.time()
rotor.run_driver()
#rotor.check_partials(compact_print=True, step=1e-6, form='central')
refBlade.write_ontology(fname_output, rotor['blade_out'], refBlade.wt_ref)
print('Run Time = ', time.time() - tt)
print('AEP =', rotor['AEP'])
print('diameter =', rotor['diameter'])
print('ratedConditions.V =', rotor['rated_V'])
print('ratedConditions.Omega =', rotor['rated_Omega'])
print('ratedConditions.pitch =', rotor['rated_pitch'])
print('ratedConditions.T =', rotor['rated_T'])
print('ratedConditions.Q =', rotor['rated_Q'])
print('mass_one_blade =', rotor['mass_one_blade'])
print('mass_all_blades =', rotor['mass_all_blades'])
print('I_all_blades =', rotor['I_all_blades'])
print('freq =', rotor['freq_pbeam'])
print('tip_deflection =', rotor['tip_deflection'])
print('root_bending_moment =', rotor['root_bending_moment'])
print('LCoE: \t\t\t %f\t%f USD/MWh \t Difference: %f %%' % (prob_ref['lcoe']*1.e003, prob['lcoe']*1.e003, (prob['lcoe']-prob_ref['lcoe'])/prob_ref['lcoe']*100.))
print('Blade cost: \t\t\t %f\t%f USD \t Difference: %f %%' % (prob_ref['total_blade_cost'], prob['total_blade_cost'], (prob['total_blade_cost']-prob_ref['total_blade_cost'])/prob_ref['total_blade_cost']*100.))
print('Blade mass: \t\t\t %f\t%f kg \t Difference: %f %%' % (prob_ref['total_blade_mass'], prob['total_blade_mass'], (prob['total_blade_mass']-prob_ref['total_blade_mass'])/prob_ref['total_blade_mass']*100.))
print('Tower cost: \t\t\t %f\t%f USD \t Difference: %f %%' % (prob_ref['tower_cost'], prob['tower_cost'], (prob['tower_cost']-prob_ref['tower_cost'])/prob_ref['tower_cost']*100.))
print('Tower mass: \t\t\t %f\t%f kg \t Difference: %f %%' % (prob_ref['tower_mass'], prob['tower_mass'], (prob['tower_mass']-prob_ref['tower_mass'])/prob_ref['tower_mass']*100.))
# ----------------------
else:
# If not optimizing, plot current design
prob = prob_ref
show_plots = True
flag_write_out = False
if flag_write_out:
# --- Save output .yaml ---
refBlade.write_ontology(fname_output, prob['blade_out'], refBlade.wt_ref)
shutil.copyfile(fname_input, folder_output + os.sep + fname_output)
def format_save(fig, fig_name):
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
plt.grid(color=[0.8,0.8,0.8], linestyle='--')
plt.subplots_adjust(bottom = 0.15, left = 0.15)
fig.savefig(folder_output + os.sep + fig_name+'.pdf', pad_inches=0.1, bbox_inches='tight')
fig.savefig(folder_output + os.sep + fig_name+'.png', pad_inches=0.1, bbox_inches='tight')
# Problem initialization
var_y = ['chord','theta','rthick','p_le','precurve','presweep']
label_y = ['Chord [m]', 'Twist [deg]', 'Relative Thickness [%]', 'Pitch Axis Chord Location [%]', 'Prebend [m]', 'Sweep [m]']
scaling_factor = [1. , 1. , 100. , 100., 1., 1.]