示例#1
0
文件： 1pvwatts.py 项目： acmbc68/omf 
from sscapi import PySSC
import matplotlib.pyplot as plot

# setup data structures
ssc = PySSC()
dat = ssc.data_create()
# required inputs
ssc.data_set_string(dat, "file_name", "daggett.tm2")
ssc.data_set_number(dat, "system_size", 4)
ssc.data_set_number(dat, "derate", 0.77)
ssc.data_set_number(dat, "track_mode", 2)
ssc.data_set_number(dat, "azimuth", 180)
ssc.data_set_number(dat, "tilt_eq_lat", 1)
# default inputs exposed
ssc.data_set_number(dat, 'rotlim', 45.0)
ssc.data_set_number(dat, 't_noct', 45.0)
ssc.data_set_number(dat, 't_ref', 25.0)
ssc.data_set_number(dat, 'gamma', -0.5)
ssc.data_set_number(dat, 'inv_eff', 0.92)
ssc.data_set_number(dat, 'fd', 1.0)
ssc.data_set_number(dat, 'i_ref', 1000)
ssc.data_set_number(dat, 'poa_cutin', 0)
ssc.data_set_number(dat, 'w_stow', 0)
# complicated optional inputs
# ssc.data_set_array(dat, 'shading_hourly', ...) 	Hourly beam shading factors
# ssc.data_set_matrix(dat, 'shading_mxh', ...) 		Month x Hour beam shading factors
# ssc.data_set_matrix(dat, 'shading_azal', ...) 	Azimuth x altitude beam shading factors
# ssc.data_set_number(dat, 'shading_diff', ...) 	Diffuse shading factor
# ssc.data_set_number(dat, 'enable_user_poa', ...)	Enable user-defined POA irradiance input = 0 or 1
# ssc.data_set_array(dat, 'user_poa', ...) 			User-defined POA irradiance in W/m2
示例#2
0
from sscapi import PySSC

# setup inputs
ssc = PySSC()
dat = ssc.data_create()
ssc.data_set_string(dat, "file_name", "daggett.tm2")
ssc.data_set_number(dat, "system_size", 4)
ssc.data_set_number(dat, "derate", 0.77)
ssc.data_set_number(dat, "track_mode", 0)
ssc.data_set_number(dat, "azimuth", 180)
ssc.data_set_number(dat, "tilt_eq_lat", 1)
ssc.data_set_matrix(dat, "shading_mxh",
                    [[
                        0, 0, 0, 0, 0, 0, 0, 0, 0.475, 0.95, 1, 1, 0.7875,
                        0.2375, 0.25, 0.3625, 0, 0, 0, 0, 0, 0, 0, 0
                    ],
                     [
                         0, 0, 0, 0, 0, 0, 0, 0, 0.4875, 1, 1, 1, 0.925,
                         0.6375, 0.6625, 0.225, 0, 0, 0, 0, 0, 0, 0, 0
                     ],
                     [
                         0, 0, 0, 0, 0, 0, 0, 0.15, 0.925, 1, 1, 1, 1, 1, 0.75,
                         0.2, 0, 0, 0, 0, 0, 0, 0, 0
                     ],
                     [
                         0, 0, 0, 0, 0, 0, 0, 0.45, 0.9125, 1, 1, 1, 1, 1,
                         0.625, 0.375, 0, 0, 0, 0, 0, 0, 0, 0
                     ],
                     [
                         0, 0, 0, 0, 0, 0.075, 0.05, 0.7875, 1, 1, 1, 1, 1, 1,
                         0.625, 0.4875, 0.025, 0, 0, 0, 0, 0, 0, 0
示例#3
0
文件： 2swh.py 项目： acmbc68/omf 
from sscapi import PySSC
from matplotlib import pyplot as pyp

# setup data structures.
ssc = PySSC()
dat = ssc.data_create()
# required inputs.
ssc.data_set_string(dat, "file_name", "daggett.tm2")
# todo: take hot water array input from GUI.
hotWaterArray = 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05,7.26,7.52,8.84,11.6,13.7,13.8,12.5,11,8.65,5.85,2.7,1.27,0.951,1.11,2.31,7.74,17.8,19.9,18.1,15.4,12.8,10.7,9.1,8.05,7.26,7.52,8.84,11.6,13.7,13.8,12.5,11,8.65,5.85,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.7,1.27,0.951,1.11,2.31,7.74,17.8,19.9,18.1,15.4,12.8,10.7,9.1,8.05,7.26,7.52,8.84,11.6,13.7,13.8,12.5,11,8.65,5.85,2.7,1.27,0.951,1.11,2.31,7.74,17.8,19.9,18.1,15.4,12.8,10.7,9.1,8.05,7.26,7.52,8.84,11.6,13.7,13.8,12.5,11,8.65,5.85,2.7,1.27,0.951,1.11,2.31,7.74,17.8,19.9,18.1,15.4,12.8,10.7,9.1,8.05,7.26,7.52,8.84,11.6,13.7,13.8,12.5,11,8.65,5.85,2.7,1.27,0.951,1.11,2.31,7.74,17.8,19.9,18.1,15.4,12.8,10.7,9.1,8.05,7.26,7.52,8.84,11.6,13.7,13.8,12.5,11,8.65,5.85,2.97,1.4,1.05,1.22,2.54,8.54,19.7,22,20,16.9,14.1,11.8,10,8.88,8,8.29,9.74,12.8,15.1,15.2,13.8,12.1,9.53,6.45,2.97,1.4,1.05,1.22,2.54,8.54,19.7,22,20,16.9,14.1,11.8,10,8.88,8,8.29,9.74,12.8,15.1,15.2,13.8,12.1,9.53,6.45]
ssc.data_set_array(dat,"scaled_draw", hotWaterArray)	#Hot water draw							kg/hr LENGTH=8760
ssc.data_set_number(dat, "tilt", 30) 					#Collector tilt							deg  MIN=0,MAX=90
ssc.data_set_number(dat, "azimuth", 0) 					#Collector azimuth						deg 90=E,180=S MIN=0,MAX=360
ssc.data_set_number(dat, "albedo", 0.15) 				#Ground reflectance factor				0..1 FACTOR
ssc.data_set_number(dat, "irrad_mode", 0) 				#Irradiance input mode					0/1 Beam+Diff,Global+Beam ?=0 INTEGER,MIN=0,MAX=1
ssc.data_set_number(dat, "sky_model", 2) 				#Tilted surface irradiance model		0/1/2 Isotropic,HDKR,Perez ?=2 INTEGER,MIN=0,MAX=2
ssc.data_set_number(dat, "mdot", 0.0617) 				#Total system mass flow rate			kg/s POSITIVE
ssc.data_set_number(dat, "ncoll", 4) 					#Number of collectors					Unitless POSITIVE,INTEGER
ssc.data_set_number(dat, "fluid", 0) 					#Working fluid in system				Water,Glycol (INTEGER,MIN=0,MAX=1)
ssc.data_set_number(dat, "area_coll", 11.2) 			#Single collector area					m2 POSITIVE
ssc.data_set_number(dat, "test_fluid", 0) 				#Fluid used in collector test			Water,Glycol (INTEGER,MIN=0,MAX=1)
ssc.data_set_number(dat, "test_flow", 0.0417) 			#Flow rate used in collector test		kg/s POSITIVE
ssc.data_set_number(dat, "pipe_length", 20) 			#Length of piping in system				m POSITIVE
ssc.data_set_number(dat, "pipe_diam", 0.07) 			#Pipe diameter							m POSITIVE
ssc.data_set_number(dat, "pipe_k", 0.02) 				#Pipe insulation conductivity			W/m2.C POSITIVE
ssc.data_set_number(dat, "pipe_insul", 0.1) 			#Pipe insulation thickness				m POSITIVE
ssc.data_set_number(dat, "tank_h2d_ratio", 3) 			#Solar tank height to diameter ratio	Unitless POSITIVE
ssc.data_set_number(dat, "U_tank", 3.553) 				#Solar tank heat loss coefficient		W/m2K POSITIVE
ssc.data_set_number(dat, "V_tank", 1) 					#Solar tank volume						m3 POSITIVE
ssc.data_set_number(dat, "hx_eff", 0.5) 				#Heat exchanger effectiveness			0..1 POSITIVE
ssc.data_set_number(dat, "T_room", 18.3) 				#Ambient temperature in mech room		C POSITIVE
示例#4
0
文件： solarTSPPA.py 项目： acmbc68/omf 
print num_series
print num_inverters



# set the weather file.  the web service should take a 
# lat-long and use the perez satellite data or tmy2/3 data
# in the same way that the PVWatts service specifies the weather data
# --> essentially, this service and PVWatts should use exactly the same
#     method to get weather data for a location request

ssc = PySSC()
data = ssc.data_create()

ssc.data_set_string(data, 'weather_file', 'daggett.tm2' )
ssc.data_set_number(data, 'ac_derate', ac_derate )
ssc.data_set_number(data, 'modules_per_string', num_series )
ssc.data_set_number(data, 'strings_in_parallel', num_parallel )
ssc.data_set_number(data, 'inverter_count', num_inverters )
ssc.data_set_number(data, 'subarray1_tilt', tilt )
ssc.data_set_number(data, 'subarray1_azimuth', azimuth )
ssc.data_set_number(data, 'subarray1_track_mode', track_mode )
ssc.data_set_matrix(data, 'subarray1_shading_mxh', shading_mxh )
ssc.data_set_array(data, 'subarray1_soiling', [soiling, soiling, soiling, soiling, soiling, soiling, soiling, soiling, soiling, soiling, soiling, soiling ] )
ssc.data_set_number(data, 'subarray1_derate', dc_derate )

# set up values for other sub arrays - not used (currently)
ssc.data_set_number(data, 'subarray2_tilt', 0 )
ssc.data_set_number(data, 'subarray3_tilt', 0 )
ssc.data_set_number(data, 'subarray4_tilt', 0 )
示例#5
0
from sscapi import PySSC
''' This does not work because of API failures as of 3/22/2013 '''

ssc = PySSC()
data = ssc.data_create()

# Test windwatts with skystream 2.4/3.7 hybrid
ssc.data_set_string(data, 'file_name', 'WY Southern-Flat Lands.srw')
ssc.data_set_number(data, 'ctl_mode', 2)
ssc.data_set_number(data, 'cutin', 4)
ssc.data_set_number(data, 'hub_ht', 50)
ssc.data_set_number(data, 'lossc', 0)
ssc.data_set_number(data, 'lossp', 0)
pc_wind = [
    0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
    21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39
]
ssc.data_set_array(data, 'pc_wind', pc_wind)
pc_power = [
    0, 0, 0, 0, 0.08, 0.02, 0.35, 0.6, 1, 1.6, 2, 2.25, 2.35, 2.4, 2.4, 2.37,
    2.3, 2.09, 2, 2, 2, 2, 2, 1.98, 1.95, 1.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0
]
ssc.data_set_array(data, 'pc_power', pc_power)
ssc.data_set_number(data, 'rotor_di', 3.7)
ssc.data_set_number(data, 'shear', 0.14)
ssc.data_set_number(data, 'turbul', 0.1)
ssc.data_set_array(data, 'wt_x', [0])
ssc.data_set_array(data, 'wt_y', [0])
ssc.data_set_number(data, 'wake_model', 0)
ssc.data_set_number(data, 'model_choice', 0)
示例#6
0
文件： 1pvwatts.py 项目： cdkkim/omf 
from sscapi import PySSC
import matplotlib.pyplot as plot

# setup data structures
ssc = PySSC()
dat = ssc.data_create()
# required inputs
ssc.data_set_string(dat, "file_name", "daggett.tm2")
ssc.data_set_number(dat, "system_size", 4)
ssc.data_set_number(dat, "derate", 0.77)
ssc.data_set_number(dat, "track_mode", 2)
ssc.data_set_number(dat, "azimuth", 180)
ssc.data_set_number(dat, "tilt_eq_lat", 1)
# default inputs exposed
ssc.data_set_number(dat, 'rotlim', 45.0)
ssc.data_set_number(dat, 't_noct', 45.0)
ssc.data_set_number(dat, 't_ref', 25.0)
ssc.data_set_number(dat, 'gamma', -0.5)
ssc.data_set_number(dat, 'inv_eff', 0.92)
ssc.data_set_number(dat, 'fd', 1.0)
ssc.data_set_number(dat, 'i_ref', 1000)
ssc.data_set_number(dat, 'poa_cutin', 0)
ssc.data_set_number(dat, 'w_stow', 0)
# complicated optional inputs
# ssc.data_set_array(dat, 'shading_hourly', ...) 	Hourly beam shading factors
# ssc.data_set_matrix(dat, 'shading_mxh', ...) 		Month x Hour beam shading factors
# ssc.data_set_matrix(dat, 'shading_azal', ...) 	Azimuth x altitude beam shading factors
# ssc.data_set_number(dat, 'shading_diff', ...) 	Diffuse shading factor
# ssc.data_set_number(dat, 'enable_user_poa', ...)	Enable user-defined POA irradiance input = 0 or 1
# ssc.data_set_array(dat, 'user_poa', ...) 			User-defined POA irradiance in W/m2
示例#7
0
from sscapi import PySSC

# setup inputs
ssc = PySSC()
dat = ssc.data_create()
ssc.data_set_string(dat, "file_name", "daggett.tm2")
ssc.data_set_number(dat, "system_size", 4)
ssc.data_set_number(dat, "derate", 0.77)
ssc.data_set_number(dat, "track_mode", 0)
ssc.data_set_number(dat, "azimuth", 180)
ssc.data_set_number(dat, "tilt_eq_lat", 1)
ssc.data_set_array(dat, "shading_hourly", [0.9 for x in range(0,8760)])

# run PV system simulation
mod = ssc.module_create("pvwattsv1")
ssc.module_exec(mod, dat)

# print results
ann = 0
ac = ssc.data_get_array(dat, "ac")
for i in range(len(ac)):
	ac[i] = ac[i]/1000
	ann += ac[i]
print "PVWatts V1 Simulation ok, e_net (annual kW)=", ann
示例#8
0
print num_parallel
print num_series
print num_inverters

# set the weather file.  the web service should take a
# lat-long and use the perez satellite data or tmy2/3 data
# in the same way that the PVWatts service specifies the weather data
# --> essentially, this service and PVWatts should use exactly the same
#     method to get weather data for a location request

ssc = PySSC()
data = ssc.data_create()

ssc.data_set_string(data, 'weather_file', 'daggett.tm2')
ssc.data_set_number(data, 'ac_derate', ac_derate)
ssc.data_set_number(data, 'modules_per_string', num_series)
ssc.data_set_number(data, 'strings_in_parallel', num_parallel)
ssc.data_set_number(data, 'inverter_count', num_inverters)
ssc.data_set_number(data, 'subarray1_tilt', tilt)
ssc.data_set_number(data, 'subarray1_azimuth', azimuth)
ssc.data_set_number(data, 'subarray1_track_mode', track_mode)
ssc.data_set_matrix(data, 'subarray1_shading_mxh', shading_mxh)
ssc.data_set_array(data, 'subarray1_soiling', [
    soiling, soiling, soiling, soiling, soiling, soiling, soiling, soiling,
    soiling, soiling, soiling, soiling
])
ssc.data_set_number(data, 'subarray1_derate', dc_derate)

# set up values for other sub arrays - not used (currently)
ssc.data_set_number(data, 'subarray2_tilt', 0)
示例#9
0
def sam_simulation(nsrdb_data, meta=None, verbose=False, **kwargs):
    """SAM solar PV simulation

    Perform a PVWATTS5 simulation using some input information about the
    solar plant.

    Parameters
    ----------
        weather (pd.DataFrame): Solar radiation dataframe
        meta (pd.DataFrame): NSRDB metadata
        kwargs (dictionary): Dictionary containing simulation parameters

    Returns
    ----------
        CF (float): Capacity factor
        Generation (float): Generation over the year of simulation
        meto_data (pd.DataFrame): Dataframe with hourly generation
    """

    params = {
        "lat": kwargs["lat"],
        "lng": kwargs["lon"],
        "system_capacity": kwargs["system_capacity"],
        "dc_ac_ratio": kwargs["dc_ac_ratio"],
        "inv_eff": kwargs["inv_eff"],
        "losses": kwargs["losses"],
        "tilt": kwargs["tilt"],
        "gcr": kwargs["gcr"],
        "azimuth": kwargs["azimuth"],
        "interval": kwargs["interval"],
    }
    if verbose:
        print({key: value for key, value in params.items()})

    # Start sscapi module
    ssc = PySSC()
    weather_data = ssc.data_create()
    valid_keys = [
        "lat",
        "lon",
        "tz",
        "elev",
    ]
    for key, value in kwargs.items():
        bytestr = key.encode()  # Convert string to byte to read it on C
        if key in valid_keys:
            ssc.data_set_number(weather_data, bytestr, value)
    # Set tilt of system in degrees
    ssc.data_set_array(weather_data, b"year", nsrdb_data.index.year)
    ssc.data_set_array(weather_data, b"month", nsrdb_data.index.month)
    ssc.data_set_array(weather_data, b"day", nsrdb_data.index.day)
    ssc.data_set_array(weather_data, b"hour", nsrdb_data.index.hour)
    ssc.data_set_array(weather_data, b"minute", nsrdb_data.index.minute)
    ssc.data_set_array(weather_data, b"dn", nsrdb_data["DNI"])
    ssc.data_set_array(weather_data, b"df", nsrdb_data["DHI"])
    ssc.data_set_array(weather_data, b"wspd", nsrdb_data["Wind Speed"])
    ssc.data_set_array(weather_data, b"tdry", nsrdb_data["Temperature"])

    # Create SAM compliant object
    sam_data = ssc.data_create()
    ssc.data_set_table(sam_data, b"solar_resource_data", weather_data)
    ssc.data_free(weather_data)
    valid_keys = [
        "system_capacity",  # kW
        "dc_ac_ratio",
        "array_type",
        "inv_eff",
        "losses",
        "gcr",
        "tilt",
        "azimuth",
        "interval",
        "adjust:constant",
    ]
    for key, value in kwargs.items():
        bytestr = key.encode()  # Convert string to byte to read it on C
        if key in valid_keys:
            ssc.data_set_number(sam_data, bytestr, value)
    if kwargs["model"] == "pvwattsv7" and "module_type" in kwargs:
        ssc.data_set_number(sam_data, b"module_type",
                            kwargs.get("module_type", 0))
    mod = ssc.module_create(kwargs.get("model").encode())

    ssc.module_exec(mod, sam_data)

    nsrdb_data["ac_generation_W"] = np.array(
        ssc.data_get_array(sam_data, b"ac"))
    nsrdb_data["dc_generation_W"] = np.array(
        ssc.data_get_array(sam_data, b"dc"))
    nsrdb_data["dc_capacity_factor"] = (nsrdb_data["dc_generation_W"] *
                                        1e3) / kwargs["system_capacity"]
    nsrdb_data["POA"] = np.array(ssc.data_get_array(sam_data, b"poa"))

    # Module temperature in ºC
    nsrdb_data["TCell"] = np.array(ssc.data_get_array(sam_data, b"tcell"))

    # free the memory
    ssc.data_free(sam_data)
    ssc.module_free(mod)

    return nsrdb_data
示例#10
0
文件： geothermal.py 项目： acmbc68/omf 
from sscapi import PySSC

''' Runs but returns nonsense data. '''

# setup inputs
ssc = PySSC()
dat = ssc.data_create()
ssc.data_set_string(dat, "file_name", "daggett.tm2")
ssc.data_set_number(dat, "resource_potential", 910)				#Resource Potential	MW
ssc.data_set_number(dat, "resource_type", 0)					#Type of Resource			INTEGER
ssc.data_set_number(dat, "resource_temp", 200)					#Resource Temperature	C
ssc.data_set_number(dat, "resource_depth", 2000)				#Resource Depth	m
ssc.data_set_number(dat, "analysis_period", 25)					#Analysis Lifetime	years		INTEGER
ssc.data_set_number(dat, "model_choice", 0)						#Which model to run (0,1,2)			INTEGER
ssc.data_set_number(dat, "nameplate", 15000)					#Desired plant output	kW
ssc.data_set_number(dat, "analysis_type", 0)					#Analysis Type			INTEGER
ssc.data_set_number(dat, "num_wells", 3)						#Number of Wells
ssc.data_set_number(dat, "num_wells_getem", 3)					#Number of Wells GETEM calc'd
ssc.data_set_number(dat, "conversion_type", 0)					#Conversion Type			INTEGER
ssc.data_set_number(dat, "plant_efficiency_input", 11.28)		#Plant efficiency
ssc.data_set_number(dat, "conversion_subtype", 0)				#Conversion Subtype			INTEGER
ssc.data_set_number(dat, "decline_type", 0)						#Temp decline Type			INTEGER
ssc.data_set_number(dat, "temp_decline_rate", 0.03)				#Temperature decline rate	%/yr
ssc.data_set_number(dat, "temp_decline_max", 30)				#Maximum temperature decline	C
ssc.data_set_number(dat, "wet_bulb_temp", 15)					#Wet Bulb Temperature	C
ssc.data_set_number(dat, "ambient_pressure", 14.7)				#Ambient pressure	psi
ssc.data_set_number(dat, "well_flow_rate", 70)					#Production flow rate per well	kg/s
ssc.data_set_number(dat, "pump_efficiency", 0.60)				#Pump efficiency	%
ssc.data_set_number(dat, "delta_pressure_equip", 25)			#Delta pressure across surface equipment	psi
ssc.data_set_number(dat, "excess_pressure_pump", 50.76)			#Excess pressure @ pump suction	psi
ssc.data_set_number(dat, "well_diameter", 10)					#Production well diameter	in
示例#11
0
文件： geothermal.py 项目： cdkkim/omf 
from sscapi import PySSC
''' Runs but returns nonsense data. '''

# setup inputs
ssc = PySSC()
dat = ssc.data_create()
ssc.data_set_string(dat, "file_name", "daggett.tm2")
ssc.data_set_number(dat, "resource_potential", 910)  #Resource Potential	MW
ssc.data_set_number(dat, "resource_type", 0)  #Type of Resource			INTEGER
ssc.data_set_number(dat, "resource_temp", 200)  #Resource Temperature	C
ssc.data_set_number(dat, "resource_depth", 2000)  #Resource Depth	m
ssc.data_set_number(dat, "analysis_period",
                    25)  #Analysis Lifetime	years		INTEGER
ssc.data_set_number(dat, "model_choice",
                    0)  #Which model to run (0,1,2)			INTEGER
ssc.data_set_number(dat, "nameplate", 15000)  #Desired plant output	kW
ssc.data_set_number(dat, "analysis_type", 0)  #Analysis Type			INTEGER
ssc.data_set_number(dat, "num_wells", 3)  #Number of Wells
ssc.data_set_number(dat, "num_wells_getem", 3)  #Number of Wells GETEM calc'd
ssc.data_set_number(dat, "conversion_type", 0)  #Conversion Type			INTEGER
ssc.data_set_number(dat, "plant_efficiency_input", 11.28)  #Plant efficiency
ssc.data_set_number(dat, "conversion_subtype",
                    0)  #Conversion Subtype			INTEGER
ssc.data_set_number(dat, "decline_type", 0)  #Temp decline Type			INTEGER
ssc.data_set_number(dat, "temp_decline_rate",
                    0.03)  #Temperature decline rate	%/yr
ssc.data_set_number(dat, "temp_decline_max",
                    30)  #Maximum temperature decline	C
ssc.data_set_number(dat, "wet_bulb_temp", 15)  #Wet Bulb Temperature	C
ssc.data_set_number(dat, "ambient_pressure", 14.7)  #Ambient pressure	psi
ssc.data_set_number(dat, "well_flow_rate",