InvCecCg¶
Wrapper for SAM Simulation Core model: cmod_inv_cec_cg.cpp
Creating an Instance¶
There are three methods to create a new instance of a PySAM module. Using default populates the newclass’ attributes with default values specific to a config. Each technology-financialconfiguration corresponds to a SAM GUI configuration. Using new creates an instance with empty attributes. The wrap function allows compatibility with PySSC, for details, refer to PySSC.
InvCecCg model description
InvCecCg
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PySAM.InvCecCg.default(config) → InvCecCg¶ Use financial config-specific default attributes
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PySAM.InvCecCg.from_existing(data, optional config) → InvCecCg¶ Share underlying data with an existing PySAM class. If config provided, default attributes are loaded otherwise.
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PySAM.InvCecCg.new() → InvCecCg¶
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PySAM.InvCecCg.wrap(ssc_data_t) → InvCecCg¶ Use existing PySSC data
Warning
Do not call PySSC.data_free on the ssc_data_t provided to
wrap
Functions¶
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class
PySAM.InvCecCg.InvCecCg¶ 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 = { 'Common': { 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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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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Common Group¶
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class
PySAM.InvCecCg.InvCecCg.Common¶ -
assign() → None¶ Assign attributes from dictionary
Common_vals = { var: val, ...}
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export() → dict¶ Export attributes into dictionary
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inv_cec_cg_paco¶ Rated max output [W]
Required: True
Type: float
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inv_cec_cg_sample_power_units¶ Sample data units for power output [0=W,1=kW]
Constraints: INTEGER,MIN=0,MAX=1
Required: If not provided, assumed to be 0
Type: float
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inv_cec_cg_test_samples¶ Sample data
Required: True
Type: sequence[sequence]
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Outputs Group¶
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class
PySAM.InvCecCg.InvCecCg.Outputs¶ -
assign() → None¶ Assign attributes from dictionary
Outputs_vals = { var: val, ...}
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export() → dict¶ Export attributes into dictionary
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Pdco¶ CEC generated Pdco [Wac]
Type: float
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Pso¶ CEC generated Pso [Wdc]
Type: float
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Vdco¶ CEC generated Vdco [Vdc]
Type: float
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c0¶ CEC generated c0 [1/W]
Type: float
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c1¶ CEC generated c1 [1/V]
Type: float
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c2¶ CEC generated c2 [1/V]
Type: float
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c3¶ CEC generated c3 [1/V]
Type: float
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inv_cec_cg_C0¶ C0 at Vmin, Vnom, Vmax
Type: sequence
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inv_cec_cg_C1¶ C1 at m and b
Type: sequence
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inv_cec_cg_C2¶ C1 at m and b
Type: sequence
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inv_cec_cg_C3¶ C1 at m and b
Type: sequence
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inv_cec_cg_Pdco¶ Pdco at Vmin, Vnom, Vmax
Type: sequence
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inv_cec_cg_Psco¶ Psco at Vmin, Vnom, Vmax
Type: sequence
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inv_cec_cg_Vdc¶ Vdc at Vmin, Vnom, Vmax
Type: sequence
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inv_cec_cg_Vdc_Vnom¶ Vdc - Vnom at Vmin, Vnom, Vmax
Type: sequence
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inv_cec_cg_Vmax¶ Vmax for least squares fit
Type: sequence[sequence]
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inv_cec_cg_Vmax_abc¶ Vmax a,b,c for least squares fit
Type: sequence
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inv_cec_cg_Vmin¶ Vmin for least squares fit
Type: sequence[sequence]
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inv_cec_cg_Vmin_abc¶ Vmin a,b,c for least squares fit
Type: sequence
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inv_cec_cg_Vnom¶ Vnom for least squares fit
Type: sequence[sequence]
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inv_cec_cg_Vnom_abc¶ Vnom a,b,c for least squares fit
Type: sequence
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