def setUp(self):
fn = 'TestExternalPyStr.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=4, step=1)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
fn = 'TestTMY3WeatherFileChecker.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=1, step=5)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
fn = 'TestPolynomial.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=10, step=0.1)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
fn = 'TestCatromOE.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop='1y', step=300)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
fn = 'TestGraphiteProperty.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=3, step=0.01)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self): fn = 'TestWeatherSource.mo' sim = simulation.Simulator(fn) sim.compile_model() sim.compile_sim(args=['-s']) sim.simulate(start=0, stop=86400, step=40) self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self): fn = '../examples/Reference_2.mo' sim = simulation.Simulator(fn) sim.compile_model() sim.compile_sim(args=['-s']) sim.simulate(start=0, stop='1y', step='5m',solver='dassl', nls='newton') self.res = postproc.SimResultElec(sim.res_fn) self.perf = self.res.calc_perf()
def setUp(self): fn = '../examples/SaltSCO2System.mo' sim = simulation.Simulator(fn) sim.compile_model() sim.compile_sim(args=['-s']) sim.simulate(start=0, stop='1y', step='300s',solver='dassl', nls='homotopy') self.res = postproc.SimResultElec(sim.res_fn) self.perf = self.res.calc_perf()
def setUp(self):
#self.cwd = os.chdir(os.path.dirname(__file__))
fn = 'TestSTTable.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=4, step=0.01)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
fn = 'TestSolarPosition.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
# One year ~500 intervals per day:
sim.simulate(start=0, stop=31536000, step=170)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
fn = '../examples/SolarFuelSystem.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop='1y', step='5m')
self.res = postproc.SimResultFuel(sim.res_fn)
self.perf = self.res.calc_perf()
def setUp(self):
print("RUNNING SETUP")
fn = 'TestCatromOE.mo'
sim = simulation.Simulator(fn)
print("COMPILING MODEL")
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop='1y', step=300)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
fn = 'TestOptimisation.mo'
model = 'AO'
sim = simulation.Simulator(fn, model=model)
# For some reason won't compile with Modelica library
sim.compile_model(libs=[], args=['-g=Optimica'])
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=1, step=0.02, solver='optimization')
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
if os.path.isfile('TestCommandTouched'):
os.remove('TestCommandTouched')
fn = 'TestCommand.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=1, step=0.1)
self.res = postproc.SimResult(sim.model + '_res.mat')
def setUp(self):
if os.path.isfile('resources/tests/weatherfile2.motab'):
os.remove('resources/tests/weatherfile2.motab')
fn = 'TestWeatherFileChecker.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=1, step=0.01)
self.res = postproc.SimResult(sim.model + '_res.mat')
def __init__(self, moname, modir, simdir):
self.moname = moname
self.simdir = simdir
self.modir = modir
fnmo = "%s/%s.mo" % (self.modir, self.moname)
shutil.copy(fnmo, self.simdir)
os.chdir(self.simdir)
self.sim = simulation.Simulator("%s.mo" % (self.moname), suffix="0")
self.sim.compile_model()
self.sim.compile_sim()
def setUp(self): fn = '../examples/Reference_2.mo' res_fn='./Reference_2_res.mat' xml_fn='./Reference_2_init.xml' self.sm=2.8 self.t_storage=9 sim = simulation.Simulator(fn) sim.compile_model() self.pxml=ProcesXML(xml_fn) self.pxml.write_par(par_n=['SM', 't_storage'], par_v=[self.sm, self.t_storage],one=False) sim.compile_sim(args=['-s']) sim.simulate(start=0, stop=10, step=0.1) self.mat=DyMat.DyMatFile(res_fn)
def test_modelica():
"""
Run the modelica test of STMotab.
"""
fn = './TestSTMotab.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop='1y', step='5m', solver='dassl', nls='homotopy')
res = DyMat.DyMatFile('TestSTMotab_res.mat')
assert res.data("t1")[0] == 31500000.
assert res.data("dnival")[0] == 976.
assert res.data("dnicol")[0] == 2.
cleantest.clean('TestSTMotab')
def test_optimum():
from solartherm import simulation
from solartherm import postproc
import cleantest
fn = 'TestOptimisation.mo'
model = 'AO'
sim = simulation.Simulator(fn, model=model)
# For some reason won't compile with Modelica library
sim.compile_model(libs=[], args=['-g=Optimica'])
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop=1, step=0.02, solver='optimization')
res = postproc.SimResult(sim.model + '_res.mat')
assert abs(res.interpolate('x1', 0) - 1.0) / 1.0 < 0.01
assert abs(res.interpolate('x2', 0) - 0.0) < 0.01
assert abs(res.interpolate('u', 1) - 2.48) / 2.48 < 0.01
cleantest.clean('AO')
def test_system():
fn = '../examples/SimpleSystemOptimalDispatch.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.simulate(start=0, stop='1y', step='5m', solver='dassl', nls='newton')
res = postproc.SimResultElec(sim.res_fn)
perf = res.calc_perf(peaker=True)
# Note these are set to the values for what is thought to be a working
# version. They are not validated against anything or independently
# calculated.
print('index, epy (MWh/year),lcoe peaker ($/MWh),capf (%),srev ($')
print(perf)
assert abs(perf[0] - 300.757) / 300.757 < 0.01 # epy
assert abs(perf[1] - 38.798) / 38.798 < 0.01 # LCOE peaker
assert abs(perf[2] - 100.09) / 100.09 < 0.01 # Capacity factor
cleantest.clean('SimpleSystemOptimalDispatch')
def test_ref2solstice():
fn = '../examples/Reference_2_solstice.mo'
sim = simulation.Simulator(fn)
sim.compile_model()
sim.compile_sim(args=['-s'])
sim.update_pars(['n_row_oelt', 'n_col_oelt'],
['3', '3']) # reduce oelt resolution
sim.simulate(start=0, stop='1y', step='5m', solver='dassl', nls='newton')
res = postproc.SimResultElec(sim.res_fn)
perf = res.calc_perf()
# Note these are set to the values for what is thought to be a working
# version. They are not validated against anything or independently
# calculated.
assert abs(perf[0] - 393933.791) / 393933.791 < 0.1 # epy
assert abs(perf[1] - 160.352) / 160.352 < 0.1 # LCOE
assert abs(perf[2] - 44.969) / 44.969 < 0.1 # Capacity factor
cleantest.clean('Reference_2_solstice')
def gather_data(inputs):
start = time.time()
modelicavarname = [
'T_in_ref_blk', 'p_high', 'PR', 'pinch_PHX', 'dTemp_HTF_PHX', 'load',
'T_HTF_in', 'T_amb_input', 'eta_gross', 'eta_Q'
]
#Reading input
P_net = inputs["P_net"]
T_in_ref_blk = inputs["T_in_ref_blk"]
p_high = inputs["p_high"]
PR = inputs["PR"]
pinch_PHX = inputs["pinch_PHX"]
dTemp_HTF_PHX = inputs["dTemp_HTF_PHX"]
numdata = inputs["numdata"]
dirres = inputs["dirres"]
new_config = inputs["status_config"]
SolarTherm_path = inputs["SolarTherm_path"]
cwd = os.getcwd()
resdir = "%s" % (dirres)
simdir = "%s/simulation" % (cwd)
#Writedown the PB design configuration
configdir = "%s/configurations" % (cwd)
fnconfig = "%s/config0.txt" % (configdir)
index = 0
if new_config == 1:
while os.path.exists(fnconfig):
index += 1
fnconfig = "%s/config%s.txt" % (configdir, index)
#Writing a new config file
f = open(fnconfig, 'w')
f.write('P_net,T_in_ref_blk,p_high,PR,pinch_PHX,dTemp_HTF_PHX\n')
f.write('%s,%s,%s,%s,%s,%s\n' %
(P_net, T_in_ref_blk, p_high, PR, pinch_PHX, dTemp_HTF_PHX))
f.close()
#Writing the resfile
if not os.path.exists(resdir):
os.makedirs(resdir)
fntrain = "%s/training_data.csv" % (resdir)
#Change dir to simulationdir
os.chdir(simdir)
mofile = 'sCO2PBCalculator_Using_JPidea'
#Range of variables
UB = [1.25, T_in_ref_blk + 20, 322.9]
LB = [0.46, T_in_ref_blk - 30, 260.9]
LHS = lib.generate_lhs(UB, LB, 3, numdata)
#Copy the mofile to simulationdir
shutil.copy("%s/Models/PowerBlocks/%s.mo" % (SolarTherm_path, mofile), ".")
#Hack mo file to change the P_net
lib.hackmofile(mofile, './', P_net, index=21)
#Compile the mofile
sim = simulation.Simulator("%s.mo" % mofile, suffix="0")
sim.compile_model()
sim.compile_sim()
resultclass = postproc.SimResultElec
#Gather training data
simulation_engine(LHS, fntrain, modelicavarname, mofile, P_net,
T_in_ref_blk, p_high, PR, pinch_PHX, dTemp_HTF_PHX, sim)
#Gather validation data
datatrain = np.genfromtxt(fntrain, delimiter=',', skip_header=1)
num = datatrain.shape[0]
numval = int(0.3 * num)
LHS = lib.generate_lhs(UB, LB, 3, numval)
fnval = "%s/validation_data.csv" % (resdir)
simulation_engine(LHS, fnval, modelicavarname, mofile, P_net, T_in_ref_blk,
p_high, PR, pinch_PHX, dTemp_HTF_PHX, sim)
inputpreprocessing = {}
inputpreprocessing["fntrain"] = fntrain
inputpreprocessing["resdir"] = resdir
processing_data(inputpreprocessing)
#return back to CWD
os.chdir(cwd)
def test1(self):
global VERBOSE, RUNSIM, PLOTME
file_name = 'PhysicalParticleCO21D'
#file_name = 'PhysicalParticleSystem1D'
fn = ('%s.mo' % (file_name, ))
print "Modelica File Name = " + fn
sim = simulation.Simulator(fn)
resfn = sim.model + '_res.mat'
print "Modelica File Result Name = " + resfn
if VERBOSE: print "RUNNING SETUP"
if RUNSIM == 1:
if VERBOSE: print "COMPILING MODEL"
sim.compile_model(args=['-d=bltdump'])
if VERBOSE: print "COMPILING SIM"
sim.compile_sim(args=['-s'])
if VERBOSE: print "SOLVING MODEL"
reporting_interval = 1800
step_string = '%fs' % (reporting_interval)
stop_time = 365 * 24 * 3600
stop_string = '%fs' % (stop_time)
sim.simulate(start=0,
stop=stop_string,
step=step_string,
maxStep='300s',
solver='dassl',
nls=None
#,lv='LOG_DEBUG,LOG_NLS,LOG_SOLVER'#,LOG_NLS_V'
)
self.res = postproc.SimResult(resfn)
resmatfile = '/home/philgun/solartherm/examples/%s' % (
resfn) #getting the res_mat file
data = DyMat.DyMatFile(
resmatfile) #getting the value inside the resmat file
data2 = DyMat.DyMatFile('/home/philgun/solartherm/examples/%s' %
('PhysicalParticleCO21D_res.mat'))
if file_name == 'PhysicalParticleSystem0D':
rcv = 'receiver.'
elif file_name == 'PhysicalParticleCO21D_v11':
rcv = 'particleReceiver1D_v11.'
else:
rcv = 'particleReceiver1D.'
pb = 'powerBlock.'
if file_name == 'PhysicalParticleSystem1D' or file_name == 'PhysicalParticleCO21D':
N = data.data(rcv +
'N')[1] #getval(rcv + 'N') # getval('%s.N' %(rcv,))
print 'Particle Receiver Discretization = %f cells' % (N)
if VERBOSE:
print("SYSTEM'S RESULTS %s" % (file_name))
print ""
name_var = 'A_field'
var = data.data(name_var)
print 'Heliostat Field Area (m.sq) = %f' % (var[1])
name_var = 'E_elec'
var = data.data(
name_var) #getval (name_var) #('%s.%s' %(sys,name_var))
print 'Energy Per Year (MWh/year) = %f' % (var[-1] * 2.778e-10)
name_var = 'E_total_loses_optical'
var = data.data('heliostatsField.E_total_loses_optical')[
-1] #getval (name_var) #('%s.%s' %(sys,name_var))
print 'Energy losses due to optical (MWh/year) = %f' % (var *
2.778e-10)
name_var = 'H_tower'
var = data.data(name_var)
print 'Tower height (m) = %f' % (var[1])
print ""
print "Receiver's Geometry"
name_var = 'A_rcv'
var = data.data(name_var)
print 'Total receiver area (m.sq) = %f' % (var[1])
name_var = 'H_rcv'
var = data.data(name_var)
print 'Receiver height (m) = %f' % (var[1])
name_var = 'A_rcv'
var = data.data(name_var)
print 'Receiver aperture area (m.sq) = %f' % (var[1])
print ""
print "PLANT'S ANALYTICS" #two type curtailments 1 shutdown the heliostat 2 defocusing
print ""
print "Energy Analytics"
name_var = 'E_resource'
var = data.data(name_var)
print "Annual Sun's Energy coming to the heliostat field before cosine loses and curtailment (MWh/year) = %f" % (
var[-1] * 2.778e-10)
name_var = 'E_helio_incident'
var = data.data(name_var)[-1]
print "Annual energy incident of the heliostat field after curtailment due to low DNI / high windspeed (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_helio_raw'
var = data.data(name_var)[-1]
print "Annual energy delivered by the heliostat field before defocusing curtailment (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_helio_net'
var = data.data(name_var)[-1]
print "Annual energy delivered by the heliostat to the receiver after every curtailments (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_recv_incident'
var = data.data(name_var)[-1]
print "Annual energy delivered to the receiver by heliostat (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_recv_net'
var = data.data(name_var)[-1]
print "Annual energy absorbed by the working fluid in the receiver (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_pb_input'
var = data.data(name_var)[-1]
print "Annual energy delivered to the power block (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_pb_gross'
var = data.data(name_var)[-1]
print "Annual energy produced by the turbine's shaft (MWh/year) = %f" % (
var * 2.778e-10)
name_var = 'E_pb_net'
var = data.data(name_var)[-1]
print "Annual net energy produced by the system (MWh/year) = %f" % (
var * 2.778e-10)
print '#################################################################################################################'
print ""
print "Efficiency Analytics"
name_var = 'eta_curtail_off'
var = data.data(name_var)[-1]
print "Annual Efficiency of the heliostat due to low DNI/high windspeed curtailment = %f" % (
var)
name_var = 'eta_optical'
var = data.data(name_var)[-1]
print "Annual Efficiency of the heliostat due to field efficiency = %f" % (
var)
name_var = 'he_av_design'
var = data.data(name_var)[1]
print "Annual Efficiency of the heliostat due availability = %f" % (
var)
name_var = 'eta_curtail_defocus'
var = data.data(name_var)[-1]
print "Annual Efficiency of the heliostat due to defocus curtailment = %f" % (
var)
if resfn == 'PhysicalParticleCO21D_res.mat' or resfn == 'PhysicalParticleSystem1D._res.mat':
print "Annual Efficiency of the receiver due to absorption = %s" % (
'N/A')
else:
name_var = 'eta_recv_abs'
var = data.data(name_var)[-1]
print "Annual Efficiency of the receiver due to absorption = %s" % (
'N/A')
name_var = 'eta_recv_thermal'
var = data.data(name_var)[-1]
print "Annual Efficiency of the receiver due to heat losses and physics phenomena in the receiver = %f" % (
var)
name_var = 'eta_storage'
var = data.data(name_var)[-1]
print "Annual Efficiency of the storage due to losses in the storage system = %f" % (
var)
name_var = 'eta_pb_gross'
var = data.data(name_var)[-1]
print "Annual Efficiency of the power block (ratio between power gross power block / heat input to the heat exchanger) = %f" % (
var)
name_var = 'eta_pb_net'
var = data.data(name_var)[-1]
print "Annual Efficiency of the power block (ratio between net power produced by power block sub system / power produced by turbine shaft) = %f" % (
var)
name_var = 'eta_solartoelec'
var = data.data(name_var)[-1]
print "Annual Efficiency of system (solar energy / generated electrical energy) = %f" % (
var)
print '#################################################################################################################'
print "TOTAL PLANT'S COST (million AUD) = %f " % (
data.data('C_cap')[1] / 1e6)
print "TOTAL EQUIPMENTS COST (million AUD) = %f " % (
data.data('C_cap_total')[1] / 1e6)
print "Contingency, indirect and construction cost constants = %f" % (
(data.data('r_contg')[1] + 1) *
(data.data('r_indirect')[1] + 1) *
(data.data('r_cons')[1] + 1))
print ""
print "Annual OnM (million AUD) = %f " % (data.data('C_year')[1] /
1e6)
print '#################################################################################################################'
print ""
print "Site's, land and heliostat field's cost (million AUD) = %f" % (
(data.data('C_field')[1] + data.data('C_site')[1] +
data.data('C_land')[1]) / 1e6)
name_var = 'C_field'
var = data.data(name_var)[1]
print 'Capital cost of the solar field (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_site'
var = data.data(name_var)[1]
print 'Capital cost of site improvement work (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_land'
var = data.data(name_var)[1]
print 'Capital cost of land (million AUD) = %f' % ((var) / 1e6)
print '#################################################################################################################'
print ""
print "Falling particle receiver sub-system cost (million AUD)= %f" % (
(data.data('C_receiver')[1]) / 1e6)
name_var = 'C_tower'
var = data.data(name_var)[1]
print 'Capital cost of the tower (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_fpr'
var = data.data(name_var)[1]
print 'Capital cost of the falling particle receiver (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_lift_rec'
var = data.data(name_var)[1]
print 'Capital cost of the receiver lift (million AUD) = %f' % (
(var) / 1e6)
print '#################################################################################################################'
print ""
print 'Storage Tank / Bin costs (million AUD)= %f' % (
(data.data('C_storage')[1]) / 1e6)
name_var = 'C_bins'
var = data.data(name_var)[1]
print 'Total capital cost hot and cold storage bins (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_particles'
var = data.data(name_var)[1]
print 'Total capital cost of the particles (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_lift_hx'
var = data.data(name_var)[1]
print 'Capital cost of the heat exchanger lift (power block) (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_lift_cold'
var = data.data(name_var)[1]
print 'Capital cost of the cold storage lift (million AUD) = %f' % (
(var) / 1e6)
print '#################################################################################################################'
if fn == 'PhysicalParticleSystem1D.mo' or fn == 'PhysicalParticleSystem0D.mo':
print 'Power Block sub-system cost (million AUD)= %f' % (
(data.data('C_pb')[1]) / 1e6)
else:
print 'Power Block sub-system cost (million AUD)= %f' % (
(data.data('C_block')[1]) / 1e6)
name_var = 'C_LTR'
var = data.data(pb + name_var)[1]
print 'Capital cost of the low temperature recuperator (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_HTR'
var = data.data(pb + name_var)[1]
print 'Capital cost of the high temperature recuperator (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_cooler'
var = data.data(pb + name_var)[1]
print 'Capital cost of the air-cooler CO2 (million AUD) = %f' % (
var / 1e6)
name_var = 'C_exchanger'
var = data.data(pb + name_var)[1]
print 'Capital cost of the main heat exchager (between CO2 and Particle) (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_generator'
var = data.data(pb + name_var)[1]
print 'Capital cost of the generator (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_mainCompressor'
var = data.data(pb + name_var)[1]
print 'Capital cost of the main compressor (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_reCompressor'
var = data.data(pb + name_var)[1]
print 'Capital cost of the recompressor (million AUD) = %f' % (
(var) / 1e6)
name_var = 'C_turbine'
var = data.data(pb + name_var)[1]
print 'Capital cost of the turbine (million AUD) = %f' % (
(var) / 1e6)
print '#################################################################################################################'
print ""
resultclass = postproc.SimResultElec #calling the class of SimResultElec in postproc.py
res = resultclass(
resfn
) #passing the resmatfile into resultclass (postproc.SimResultElec)
result = res.calc_perf(
) #calculating result by calling calc_perf function inside the resultclass class
print '#################################################################################################################'
print "Energy Per Year(MWh/year) = %f, LCOE(USD/MWh) = %f, Capacity Factor(%%)= %f, Spot Market Revenue(million USD/year) = %f" % (
result[0], result[1], result[2], result[3] / 1e6
) #printing the postproc result
#vl = ['N','T_s[1]','T_s[%d]'%(N+1,), 'mdot', 'q_solar','A_ap'
# ,'eta_rec','eps_c[%d]'%(N,)
# ,'H_drop','W_rcv','t_c_in']
#for v in vl:
# print '%s = %f' %(v,getval('revOneDPGv2LookUpTable.%s'%(v,)))
#for v in ['Qdot_rec','Qdot_inc']:
# print '%s = %f MW' %(v,getval('revOneDPGv2LookUpTable.%s'%(v,))/1e6)
#for T in ['T_in','T_out']:
# #print '%s = %f°C'%(T,getval('revOneDPGv2LookUpTable.%s'%(T,))-273.15)
#print 'T_in = %f°C'%(getval('revOneDPGv2LookUpTable.T_s[1]')-273.15)
#print 'T_out= %f°C'%(getval('revOneDPGv2LookUpTable.T_s[%d]'%(N+1,))-273.15)
if PLOTME:
import matplotlib
matplotlib.use('GTKCairo')
import matplotlib.pyplot as pl
#nr = 1; nc = 1; sp=0 #nr = number of row , nc = nuber of column, sp = space between plot
time = data.abscissa(rcv + 'eta_rec', valuesOnly=True)
eta_rec_v11 = data.data(rcv + 'eta_rec')
eta_rec_v9 = data2.data('particleReceiver1D.' + 'eta_rec')
Qdot_rec_v11 = data.data(rcv + 'Qdot_rec') * 100
Qdot_rec_v9 = data2.data('particleReceiver1D.' + 'Qdot_rec') * 100
#print type(y)
#print np.shape(y)
#print type(time)
#print np.shape(time)
#print '**********************************'
#print ''
fig = pl.figure()
#sp+=1; ax1 = pl.subplot(nr,nc,sp)
pl.xlim(170 * 24 * 3600, 173 * 24 * 3600)
pl.plot(time, eta_rec_v11, label='v_11')
pl.plot(time, eta_rec_v9, label='v_09')
pl.legend(fontsize=20)
pl.ylabel('Efficiency of the receiver', fontsize=40)
pl.xlabel('Time', fontsize=40)
pl.title('Receiver efficiency at day 170 to 172', fontsize=40)
pl.show()
pl.xlim(170 * 24 * 3600, 173 * 24 * 3600)
pl.plot(time, Qdot_rec_v11, label='v_11')
pl.plot(time, Qdot_rec_v9, label='v_09')
pl.legend(fontsize=20)
pl.ylabel('Energy (MW)', fontsize=40)
pl.xlabel('Time', fontsize=40)
pl.title('Energy absorbed by particle at day 170 to 172',
fontsize=40)
pl.show()
