Pvsandiainv
Pvsandiainv
- 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.
- 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.
- PySAM.Pvsandiainv.new() Pvsandiainv
- 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
- 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.
- assign(dict) None
Assign attributes from nested dictionary, except for Outputs
nested_dict = { 'Sandia Inverter Model': { var: val, ...}, ...}
- execute(int verbosity) None
Execute simulation with verbosity level 0 (default) or 1
- export() dict
Export attributes into nested dictionary
- get_data_ptr() Pointer
Get ssc_data_t pointer
- 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, ...}, ...}
- unassign(name) None
Unassign a value in any of the variable groups.
- value(name, optional value) None | float | dict | sequence | str
Get or set by name a value in any of the variable groups.
SandiaInverterModel Group
- class PySAM.Pvsandiainv.Pvsandiainv.SandiaInverterModel
- assign(dict) None
Assign attributes from dictionary, overwriting but not removing values.
SandiaInverterModel_vals = { var: val, ...}
- export() dict
Export attributes into dictionary.
- replace(dict) None
Replace attributes from dictionary, unassigning values not present in input
dict
.SandiaInverterModel_vals = { var: val, ...}
- c0
Defines parabolic curvature of relationship between ac power and dc power at reference conditions [1/W]
Required: True
- Type:
float
- Type:
C0
- c1
Parameter allowing Pdco to vary linearly with dc voltage input [1/V]
Required: True
- Type:
float
- Type:
C1
- c2
Parameter allowing Pso to vary linearly with dc voltage input [1/V]
Required: True
- Type:
float
- Type:
C2
- c3
Parameter allowing C0 to vary linearly with dc voltage input [1/V]
Required: True
- Type:
float
- Type:
C3
- dc
DC power input to inverter [Watt]
Required: True
- Type:
sequence
- dc_voltage
DC voltage input to inverter [Volt]
Constraints: LENGTH_EQUAL=dc
Required: True
- Type:
sequence
- paco
Max AC power rating [Wac]
Required: True
- Type:
float
- pdco
DC power level at which Paco is achieved [Wdc]
Required: True
- Type:
float
- pntare
Parasitic AC consumption [Wac]
Required: True
- Type:
float
- pso
DC power level required to start inversion [Wdc]
Required: True
- Type:
float
- vdco
DV voltage level at which Paco is achieved [Volt]
Required: True
- Type:
float
Outputs Group
- class PySAM.Pvsandiainv.Pvsandiainv.Outputs
- assign(dict) None
Assign attributes from dictionary, overwriting but not removing values.
Outputs_vals = { var: val, ...}
- export() dict
Export attributes into dictionary.
- replace(dict) None
Replace attributes from dictionary, unassigning values not present in input
dict
.Outputs_vals = { var: val, ...}
- ac
AC power output [Wac]
- Type:
sequence
- acpar
AC parasitic power [Wac]
- Type:
sequence
- cliploss
Power loss due to clipping (Wac) [Wac]
- Type:
sequence
- eff_inv
Conversion efficiency [0..1]
- Type:
sequence
- ntloss
Power loss due to night time tare loss (Wac) [Wac]
- Type:
sequence
- plr
Part load ratio [0..1]
- Type:
sequence
- soloss
Power loss due to operating power consumption (Wac) [Wac]
- Type:
sequence