Pvsandiainv¶
Pvsandiainv
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PySAM.Pvsandiainv.
default
(config) → Pvsandiainv¶ Load defaults for the configuration
config
. Available configurations are:- None
Note
Some inputs do not have default values and may be assigned a value from the variable’s Required attribute. See variable attribute descriptions below.
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PySAM.Pvsandiainv.
from_existing
(data, optional config) → Pvsandiainv¶ Share data with an existing PySAM class. If
optional config
is a valid configuration name, load the module’s defaults for that configuration.
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PySAM.Pvsandiainv.
new
() → Pvsandiainv¶
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PySAM.Pvsandiainv.
wrap
(ssc_data_t) → Pvsandiainv¶ Load data from a PySSC object.
Warning
Do not call PySSC.data_free on the ssc_data_t provided to
wrap()
Pvsandiainv is a wrapper for the SSC compute module cmod_pvsandiainv.cpp
Interdependent Variables¶
The variables listed below are interdependent with other variables. If you change the value of one of these variables, you may need to change values of other variables. The SAM user interface manages these interdependent variables, but in PySAM, it is up to you change the value of all interdependent variables so they are consistent. See Interdependent Variables for examples and details.
- None
Functions¶
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class
PySAM.Pvsandiainv.
Pvsandiainv
¶ This class contains all the variable information for running a simulation. Variables are grouped together in the subclasses as properties. If property assignments are the wrong type, an error is thrown.
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assign
(dict) → None¶ Assign attributes from nested dictionary, except for Outputs
nested_dict = { 'Sandia Inverter Model': { var: val, ...}, ...}
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execute
(int verbosity) → None¶ Execute simulation with verbosity level 0 (default) or 1
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export
() → dict¶ Export attributes into nested dictionary
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replace
(dict) → None¶ Replace attributes from nested dictionary, except for Outputs. Unassigns all values in each Group then assigns from the input dict.
nested_dict = { 'Sandia Inverter Model': { var: val, ...}, ...}
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unassign
(name) → None¶ Unassign a value in any of the variable groups.
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value
(name, optional value) → Union[None, float, dict, sequence, str]¶ Get or set by name a value in any of the variable groups.
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SandiaInverterModel Group¶
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class
PySAM.Pvsandiainv.Pvsandiainv.
SandiaInverterModel
¶ -
assign
(dict) → None¶ Assign attributes from dictionary, overwriting but not removing values.
SandiaInverterModel_vals = { var: val, ...}
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export
() → dict¶ Export attributes into dictionary.
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replace
(dict) → None¶ Replace attributes from dictionary, unassigning values not present in input
dict
.SandiaInverterModel_vals = { var: val, ...}
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c0
¶ Defines parabolic curvature of relationship between ac power and dc power at reference conditions [1/W]
Required: True
Type: float Type: C0
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c1
¶ Parameter allowing Pdco to vary linearly with dc voltage input [1/V]
Required: True
Type: float Type: C1
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c2
¶ Parameter allowing Pso to vary linearly with dc voltage input [1/V]
Required: True
Type: float Type: C2
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c3
¶ Parameter allowing C0 to vary linearly with dc voltage input [1/V]
Required: True
Type: float Type: C3
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dc
¶ DC power input to inverter [Watt]
Required: True
Type: sequence
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dc_voltage
¶ DC voltage input to inverter [Volt]
Constraints: LENGTH_EQUAL=dc
Required: True
Type: sequence
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paco
¶ Max AC power rating [Wac]
Required: True
Type: float
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pdco
¶ DC power level at which Paco is achieved [Wdc]
Required: True
Type: float
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pntare
¶ Parasitic AC consumption [Wac]
Required: True
Type: float
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pso
¶ DC power level required to start inversion [Wdc]
Required: True
Type: float
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vdco
¶ DV voltage level at which Paco is achieved [Volt]
Required: True
Type: float
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Outputs Group¶
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class
PySAM.Pvsandiainv.Pvsandiainv.
Outputs
¶ -
assign
(dict) → None¶ Assign attributes from dictionary, overwriting but not removing values.
Outputs_vals = { var: val, ...}
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export
() → dict¶ Export attributes into dictionary.
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replace
(dict) → None¶ Replace attributes from dictionary, unassigning values not present in input
dict
.Outputs_vals = { var: val, ...}
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ac
¶ AC power output [Wac]
Type: sequence
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acpar
¶ AC parasitic power [Wac]
Type: sequence
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cliploss
¶ Power loss due to clipping (Wac) [Wac]
Type: sequence
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eff_inv
¶ Conversion efficiency [0..1]
Type: sequence
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ntloss
¶ Power loss due to night time tare loss (Wac) [Wac]
Type: sequence
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plr
¶ Part load ratio [0..1]
Type: sequence
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soloss
¶ Power loss due to operating power consumption (Wac) [Wac]
Type: sequence
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