def test_deprecated_09(cec_inverter_parameters, adr_inverter_parameters): # deprecated function pvsystem.snlinverter with pytest.warns(pvlibDeprecationWarning): pvsystem.snlinverter(250, 40, cec_inverter_parameters) # deprecated function pvsystem.adrinverter with pytest.warns(pvlibDeprecationWarning): pvsystem.adrinverter(1232, 154, adr_inverter_parameters) # deprecated function pvsystem.spvwatts_ac with pytest.warns(pvlibDeprecationWarning): pvsystem.pvwatts_ac(90, 100, 0.95) # for missing temperature_model_parameters match = "Reverting to deprecated default: SAPM cell temperature" system = pvsystem.PVSystem() with pytest.warns(pvlibDeprecationWarning, match=match): system.sapm_celltemp(1, 2, 3)
def test_snlinverter(): inverters = sam_data['sandiainverter'] testinv = 'ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_' vdcs = pd.Series(np.linspace(0,50,51)) idcs = pd.Series(np.linspace(0,11,110)) pdcs = idcs * vdcs pacs = pvsystem.snlinverter(inverters[testinv], vdcs, pdcs)
def test_snlinverter(sam_data): inverters = sam_data['cecinverter'] testinv = 'ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_' vdcs = pd.Series(np.linspace(0,50,3)) idcs = pd.Series(np.linspace(0,11,3)) pdcs = idcs * vdcs pacs = pvsystem.snlinverter(vdcs, pdcs, inverters[testinv]) assert_series_equal(pacs, pd.Series([-0.020000, 132.004308, 250.000000]))
def test_snlinverter_Pnt_micro(): inverters = sam_data['cecinverter'] testinv = 'Enphase_Energy__M250_60_2LL_S2x___ZC____NA__208V_208V__CEC_2013_' vdcs = pd.Series(np.linspace(0,50,3)) idcs = pd.Series(np.linspace(0,11,3)) pdcs = idcs * vdcs pacs = pvsystem.snlinverter(inverters[testinv], vdcs, pdcs) assert_series_equal(pacs, pd.Series([-0.043000, 132.545914746, 240.000000]))
def test_snlinverter_float(): inverters = sam_data['cecinverter'] testinv = 'ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_' vdcs = 25. idcs = 5.5 pdcs = idcs * vdcs pacs = pvsystem.snlinverter(inverters[testinv], vdcs, pdcs) assert_almost_equals(pacs, 132.004278, 5)
def test_snlinverter(): inverters = sam_data['cecinverter'] testinv = 'ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_' vdcs = pd.Series(np.linspace(0,50,3)) idcs = pd.Series(np.linspace(0,11,3)) pdcs = idcs * vdcs pacs = pvsystem.snlinverter(inverters[testinv], vdcs, pdcs) assert_series_equal(pacs, pd.Series([-0.020000, 132.004308, 250.000000]))
def AC_out(p_dc): ## Get list of inverters sapm_inverters = pvsystem.retrieve_sam('sandiainverter') ## Choose inverter (e.g. ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014) sapm_inverter = sapm_inverters[ 'ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_'] ## Run SAPM model p_ac = pvsystem.snlinverter(p_dc.v_mp, p_dc.p_mp, sapm_inverter) return (p_ac)
def basic_chain(times, latitude, longitude, module_parameters, inverter_parameters, irradiance=None, weather=None, surface_tilt=None, surface_azimuth=None, orientation_strategy=None, transposition_model='haydavies', solar_position_method='nrel_numpy', airmass_model='kastenyoung1989', altitude=None, pressure=None, **kwargs): """ An experimental function that computes all of the modeling steps necessary for calculating power or energy for a PV system at a given location. Parameters ---------- times : DatetimeIndex Times at which to evaluate the model. latitude : float. Positive is north of the equator. Use decimal degrees notation. longitude : float. Positive is east of the prime meridian. Use decimal degrees notation. module_parameters : None, dict or Series Module parameters as defined by the SAPM. inverter_parameters : None, dict or Series Inverter parameters as defined by the CEC. irradiance : None or DataFrame, default None If None, calculates clear sky data. Columns must be 'dni', 'ghi', 'dhi'. weather : None or DataFrame, default None If None, assumes air temperature is 20 C and wind speed is 0 m/s. Columns must be 'wind_speed', 'temp_air'. surface_tilt : None, float or Series, default None Surface tilt angles in decimal degrees. The tilt angle is defined as degrees from horizontal (e.g. surface facing up = 0, surface facing horizon = 90) surface_azimuth : None, float or Series, default None Surface azimuth angles in decimal degrees. The azimuth convention is defined as degrees east of north (North=0, South=180, East=90, West=270). orientation_strategy : None or str, default None The strategy for aligning the modules. If not None, sets the ``surface_azimuth`` and ``surface_tilt`` properties of the ``system``. Allowed strategies include 'flat', 'south_at_latitude_tilt'. Ignored for SingleAxisTracker systems. transposition_model : str, default 'haydavies' Passed to system.get_irradiance. solar_position_method : str, default 'nrel_numpy' Passed to solarposition.get_solarposition. airmass_model : str, default 'kastenyoung1989' Passed to atmosphere.relativeairmass. altitude : None or float, default None If None, computed from pressure. Assumed to be 0 m if pressure is also None. pressure : None or float, default None If None, computed from altitude. Assumed to be 101325 Pa if altitude is also None. **kwargs Arbitrary keyword arguments. See code for details. Returns ------- output : (dc, ac) Tuple of DC power (with SAPM parameters) (DataFrame) and AC power (Series). """ # use surface_tilt and surface_azimuth if provided, # otherwise set them using the orientation_strategy if surface_tilt is not None and surface_azimuth is not None: pass elif orientation_strategy is not None: surface_tilt, surface_azimuth = \ get_orientation(orientation_strategy, latitude=latitude) else: raise ValueError('orientation_strategy or surface_tilt and ' 'surface_azimuth must be provided') times = times if altitude is None and pressure is None: altitude = 0. pressure = 101325. elif altitude is None: altitude = atmosphere.pres2alt(pressure) elif pressure is None: pressure = atmosphere.alt2pres(altitude) solar_position = solarposition.get_solarposition( times, latitude, longitude, altitude=altitude, pressure=pressure, method=solar_position_method, **kwargs) # possible error with using apparent zenith with some models airmass = atmosphere.get_relative_airmass( solar_position['apparent_zenith'], model=airmass_model) airmass = atmosphere.get_absolute_airmass(airmass, pressure) dni_extra = pvlib.irradiance.get_extra_radiation(solar_position.index) aoi = pvlib.irradiance.aoi(surface_tilt, surface_azimuth, solar_position['apparent_zenith'], solar_position['azimuth']) if irradiance is None: linke_turbidity = clearsky.lookup_linke_turbidity( solar_position.index, latitude, longitude) irradiance = clearsky.ineichen(solar_position['apparent_zenith'], airmass, linke_turbidity, altitude=altitude, dni_extra=dni_extra) total_irrad = pvlib.irradiance.get_total_irradiance( surface_tilt, surface_azimuth, solar_position['apparent_zenith'], solar_position['azimuth'], irradiance['dni'], irradiance['ghi'], irradiance['dhi'], model=transposition_model, dni_extra=dni_extra) if weather is None: weather = {'wind_speed': 0, 'temp_air': 20} temps = pvsystem.sapm_celltemp(total_irrad['poa_global'], weather['wind_speed'], weather['temp_air']) effective_irradiance = pvsystem.sapm_effective_irradiance( total_irrad['poa_direct'], total_irrad['poa_diffuse'], airmass, aoi, module_parameters) dc = pvsystem.sapm(effective_irradiance, temps['temp_cell'], module_parameters) ac = pvsystem.snlinverter(dc['v_mp'], dc['p_mp'], inverter_parameters) return dc, ac
def basic_chain(times, latitude, longitude, module_parameters, inverter_parameters, irradiance=None, weather=None, surface_tilt=None, surface_azimuth=None, orientation_strategy=None, transposition_model='haydavies', solar_position_method='nrel_numpy', airmass_model='kastenyoung1989', altitude=None, pressure=None, **kwargs): """ An experimental function that computes all of the modeling steps necessary for calculating power or energy for a PV system at a given location. Parameters ---------- times : DatetimeIndex Times at which to evaluate the model. latitude : float. Positive is north of the equator. Use decimal degrees notation. longitude : float. Positive is east of the prime meridian. Use decimal degrees notation. module_parameters : None, dict or Series Module parameters as defined by the SAPM. inverter_parameters : None, dict or Series Inverter parameters as defined by the CEC. irradiance : None or DataFrame If None, calculates clear sky data. Columns must be 'dni', 'ghi', 'dhi'. weather : None or DataFrame If None, assumes air temperature is 20 C and wind speed is 0 m/s. Columns must be 'wind_speed', 'temp_air'. surface_tilt : float or Series Surface tilt angles in decimal degrees. The tilt angle is defined as degrees from horizontal (e.g. surface facing up = 0, surface facing horizon = 90) surface_azimuth : float or Series Surface azimuth angles in decimal degrees. The azimuth convention is defined as degrees east of north (North=0, South=180, East=90, West=270). orientation_strategy : None or str The strategy for aligning the modules. If not None, sets the ``surface_azimuth`` and ``surface_tilt`` properties of the ``system``. transposition_model : str Passed to system.get_irradiance. solar_position_method : str Passed to location.get_solarposition. airmass_model : str Passed to location.get_airmass. altitude : None or float If None, computed from pressure. Assumed to be 0 m if pressure is also None. pressure : None or float If None, computed from altitude. Assumed to be 101325 Pa if altitude is also None. **kwargs Arbitrary keyword arguments. See code for details. Returns ------- output : (dc, ac) Tuple of DC power (with SAPM parameters) (DataFrame) and AC power (Series). """ # use surface_tilt and surface_azimuth if provided, # otherwise set them using the orientation_strategy if surface_tilt is not None and surface_azimuth is not None: pass elif orientation_strategy is not None: surface_tilt, surface_azimuth = \ get_orientation(orientation_strategy, latitude=latitude) else: raise ValueError('orientation_strategy or surface_tilt and ' + 'surface_azimuth must be provided') times = times if altitude is None and pressure is None: altitude = 0. pressure = 101325. elif altitude is None: altitude = atmosphere.pres2alt(pressure) elif pressure is None: pressure = atmosphere.alt2pres(altitude) solar_position = solarposition.get_solarposition(times, latitude, longitude, altitude=altitude, pressure=pressure, **kwargs) # possible error with using apparent zenith with some models airmass = atmosphere.relativeairmass(solar_position['apparent_zenith'], model=airmass_model) airmass = atmosphere.absoluteairmass(airmass, pressure) dni_extra = pvlib.irradiance.extraradiation(solar_position.index) dni_extra = pd.Series(dni_extra, index=solar_position.index) aoi = pvlib.irradiance.aoi(surface_tilt, surface_azimuth, solar_position['apparent_zenith'], solar_position['azimuth']) if irradiance is None: irradiance = clearsky.ineichen( solar_position.index, latitude, longitude, zenith_data=solar_position['apparent_zenith'], airmass_data=airmass, altitude=altitude) total_irrad = pvlib.irradiance.total_irrad( surface_tilt, surface_azimuth, solar_position['apparent_zenith'], solar_position['azimuth'], irradiance['dni'], irradiance['ghi'], irradiance['dhi'], model=transposition_model, dni_extra=dni_extra) if weather is None: weather = {'wind_speed': 0, 'temp_air': 20} temps = pvsystem.sapm_celltemp(total_irrad['poa_global'], weather['wind_speed'], weather['temp_air']) dc = pvsystem.sapm(module_parameters, total_irrad['poa_direct'], total_irrad['poa_diffuse'], temps['temp_cell'], airmass, aoi) ac = pvsystem.snlinverter(inverter_parameters, dc['v_mp'], dc['p_mp']) return dc, ac
def __init__(self, panel=None, forecast_length=7, forecast_model=None): self.forecast_length = forecast_length if panel == None: self.panel = Panel() else: self.panel = panel if forecast_model == None: self.fm = GFS() else: self.fm = forecast_model self.start = pd.Timestamp(datetime.date.today(), tz=self.panel.tz) # today's date self.end = self.start + pd.Timedelta( days=forecast_length) # days from today print( "getting processed data with lat: %s, lng: %s, start:%s, end:%s" % (self.panel.latitude, self.panel.longitude, self.start, self.end)) # get forecast data forecast_data = self.fm.get_processed_data(self.panel.latitude, self.panel.longitude, self.start, self.end) ghi = forecast_data['ghi'] # get solar position time = forecast_data.index a_point = self.fm.location solpos = a_point.get_solarposition(time) # get PV(photovoltaic device) modules sandia_modules = pvsystem.retrieve_sam('SandiaMod') sandia_module = sandia_modules.Canadian_Solar_CS5P_220M___2009_ dni_extra = irradiance.get_extra_radiation( self.fm.time) # extra terrestrial radiation airmass = atmosphere.get_relative_airmass(solpos['apparent_zenith']) # POA: Plane Of Array: an image sensing device consisting of an array # (typically rectangular) of light-sensing pixels at the focal plane of a lens. # https://en.wikipedia.org/wiki/Staring_array # Diffuse sky radiation is solar radiation reaching the Earth's surface after # having been scattered from the direct solar beam by molecules or particulates # in the atmosphere. # https://en.wikipedia.org/wiki/Diffuse_sky_radiation poa_sky_diffuse = irradiance.haydavies(self.panel.surface_tilt, self.panel.surface_azimuth, forecast_data['dhi'], forecast_data['dni'], dni_extra, solpos['apparent_zenith'], solpos['azimuth']) # Diffuse reflection is the reflection of light or other waves or particles # from a surface such that a ray incident on the surface is scattered at many # angles rather than at just one angle as in the case of specular reflection. poa_ground_diffuse = irradiance.get_ground_diffuse( self.panel.surface_tilt, ghi, albedo=self.panel.albedo) # AOI: Angle Of Incidence aoi = irradiance.aoi(self.panel.surface_tilt, self.panel.surface_azimuth, solpos['apparent_zenith'], solpos['azimuth']) # irradiance is the radiant flux (power) received by a surface per unit area # https://en.wikipedia.org/wiki/Irradiance poa_irrad = irradiance.poa_components(aoi, forecast_data['dni'], poa_sky_diffuse, poa_ground_diffuse) temperature = forecast_data['temp_air'] wnd_spd = forecast_data['wind_speed'] # pvtemps: pv temperature pvtemps = pvsystem.sapm_celltemp(poa_irrad['poa_global'], wnd_spd, temperature) # irradiance actually used by PV effective_irradiance = pvsystem.sapm_effective_irradiance( poa_irrad.poa_direct, poa_irrad.poa_diffuse, airmass, aoi, sandia_module) # SAPM: Sandia PV Array Performance Model # https://pvpmc.sandia.gov/modeling-steps/2-dc-module-iv/point-value-models/sandia-pv-array-performance-model/ self.sapm_out = pvsystem.sapm(effective_irradiance, pvtemps['temp_cell'], sandia_module) sapm_inverters = pvsystem.retrieve_sam('sandiainverter') sapm_inverter = sapm_inverters[ 'ABB__MICRO_0_25_I_OUTD_US_208_208V__CEC_2014_'] self.ac_power = pvsystem.snlinverter(self.sapm_out.v_mp, self.sapm_out.p_mp, sapm_inverter)