Photovoltaic (Surrogate)

from watertap_contrib.reflo.solar_models import PVSurrogate

This Photovoltaic (PV) unit model is a surrogate model that inherits its base model structure from the Solar Energy Base Class. The model is trained using the data generated by the PV Model from PySAM which is is a Python package for the National Renewable Energy Laboratory’s System Advisor Model (SAM).

Model Structure

Outputs from the surrogate model are used to estimate the performance and the cost of the PV system.

The PV surrogate model has only 1 degree of freedom for the system capacity.

Variable	Variable Name	Symbol	Units	Description
System capacity	`system_capacity`	\(P_e\)	\(\text{kW}\)	Nameplate DC capacity of solar array

System capacity is a required input surrogate variable.

The following parameters are required outputs of the surrogate model:

Variable	Variable Name	Symbol	Units	Description
Electricity annual	`electricity_annual`	\(E_{annual}\)	\(\text{kWh}\)	Annual electric power generated by the system
Land required	`land_req`	\(A_{land}\)	\(\text{acre}\)	Land area required for the system

Additional parameters included on the PV-Battery model block are:

Parameter	Parameter Name	Symbol	Default Value	Units
DC to AC ratio	`DC_to_AC_ratio`	\(X_p\)	1.2	\(\text{kW/kW}\)

The required inverter capacity is calculated as follows:

\[P_{inv} = \frac{P_{e}}{X_{p}}\]

Note that this value may be different than the total AC inverter capacity used to generate the data for the surrogate model.

Generating Data

The data for the surrogate model can be generated using the generate_pv_data function in run_pysam_pv.py in the REFLO package. This script uses the Pvsamv1 PV model with the FlatPlatePVSingleOwner configuration to generate the data. Running this script will use the default weather file and configuration file included in the REFLO package, but users should update these files for their specific location and application. Weather files can be downloaded from the National Solar Radiation Database and configuration .json files can be created using SAM.

The generate_pv_data function takes the following arguments:

Name	Keyword	Units	Description
System capacity	`system_capacities`	\(\text{kW}\)	List of range of values of interest for the PV system capacity
Weather file	`weather_file`	N/A	Path to the weather file
Configuration file	`config_file`	N/A	Path to the configuration file for the PySAM model
Dataset file name	`dataset_filename`	N/A	Desired name of the output dataset file

from watertap_contrib.reflo.solar_models import generate_pv_data

data = generate_pv_data(
    system_capacities=[1000, 2000, 3000],
    weather_file="path/to/weather/file.csv",
    config_file="path/to/config/file.json",
    dataset_filename="path/to/dataset/filename.pkl",
)

Costing

The PV model has two costing options: simple and detailed. These are passed to the costing package through the costing_method argument when constructing the costing block. The simple costing method is the default and involves lumped capital costs from the system capacity. The detailed costing method involves more detailed capital costs including costs for the inverter, other direct costs, and sales tax.

Simple

The following parameters are constructed on the costing block for PV costing using the simple costing method:

Cost Component	Variable	Symbol	Value	Units	Description
Cost per watt installed	`cost_per_watt_installed`	\(c_{pv}\)	1.6	\(\text{USD/W}\)	Cost per watt of system capacity
Fixed operating cost per system capacity	`fixed_operating_by_capacity`	\(C_{fix,op}\)	31	\(\text{USD/kW/year}\)	Fixed operating cost of PV system per kW generated
Variable operating cost per energy generated	`variable_operating_by_generation`	\(C_{var,op}\)	0	\(\text{USD/kWh}\)	Variable operating cost of PV system per MWh generated

Cost Component	Symbol	Equation
PV system capital cost	\(C_{pv}\)	\(c_{pv} \times P_e\)
Land cost	\(C_{land}\)	\(c_{land} \times A_{land}\)
Fixed operating cost	\(C_{fix,op}\)	\(c_{fix,op} \times P_e\)

The direct costs include the cost of the PV system and land costs. Using the simple costing method, there are no indirect costs and the total capital cost is the direct costs:

\[C_{total} = C_{direct} = C_{pv} + C_{land}\]

Note that by default, REFLO assumes no land cost (i.e., \(c_{land} = 0\)).

The operating costs include both fixed and variable operating costs:

\[C_{operating} = C_{fix,op} + C_{var,op}\]

Detailed

The detailed costing method is a more direct implementation of the SAM PV costing approach. The following parameters are constructed on the costing block for PV costing using the detailed costing method:

Cost Component	Variable	Symbol	Value	Units	Description
PV module cost	`cost_per_watt_module`	\(c_{pv}\)	0.34	\(\text{USD/W}\)	Cost per watt for PV modules
Inverter cost	`cost_per_watt_inverter`	\(c_{inv}\)	0.03	\(\text{USD/W}\)	Cost per watt for inverter capacity
Other direct cost per watt	`cost_per_watt_other_direct`	\(c_{other}\)	0.62	\(\text{USD/W}\)	Cost per watt for balance of system equipment, installation labor, and margin/overhead
Indirect cost per watt	`cost_per_watt_indirect`	\(c_{indirect}\)	0.05	\(\text{USD/W}\)	Cost per watt for permitting, environmental studies, engineering, land prep, and grid interconnection
Direct cost contingency fraction	`contingency_frac_direct_cost`	\(X_{cont}\)	0.03	\(\text{dimensionless}\)	Fraction of direct costs to apply contingency
Fraction of direct capital cost subject to sales tax	`tax_frac_direct_cost`	\(X_{d}\)	1	\(\text{dimensionless}\)	Fraction of direct costs applicable for sales tax
Fixed operating cost per system capacity	`fixed_operating_by_capacity`	\(c_{fix,op}\)	31	\(\text{USD/kW/year}\)	Fixed operating cost of PV system per kW generated
Variable operating cost per energy generated	`variable_operating_by_generation`	\(c_{var,op}\)	0	\(\text{USD/kWh}\)	Variable operating cost of PV system per MWh generated

Cost Component	Symbol	Equation
PV modules capital cost	\(C_{pv}\)	\(c_{pv} \times P_e\)
PV system other capital cost	\(C_{other}\)	\(c_{other} \times P_e\)
Inverter capital cost	\(C_{inv}\)	\(c_{inv} \times P_{inv}\)
Land cost	\(C_{land}\)	\(c_{land} \times A_{land}\)
Fixed operating cost	\(C_{fix,op}\)	\(c_{fix,op} \times P_e\)
Variable operating cost	\(C_{var,op}\)	\(c_{var,op} \times E_{annual}\)

The direct costs include the cost of the PV modules, inverter, other direct costs, and contingency.

\[C_{direct} = (C_{pv} + C_{other} + C_{inv}) (1 + X_{cont})\]

Indirect costs are calculated from the system capacity and the land cost:

\[C_{indirect} = A_{land} c_{land} + P_e c_{indirect}\]

The sales tax component of the capital cost is calculated from the direct costs:

\[C_{tax} = C_{direct} X_t X_d\]

And the total capital cost is calculated with the direct costs, indirect costs, and sales tax:

\[C_{total} = C_{direct} + C_{indirect} + C_{tax}\]

Note that by default, REFLO assumes no sales tax (i.e., \(X_t = 0\)) or land cost (i.e., \(c_{land} = 0\)).

The total operating costs are the sum of fixed and variable operating costs:

\[C_{operating} = C_{fix,op} + C_{var,op}\]

Energy Balance

The PV model has only electric power flows. The steady-state electric output of the PV system is calculated as:

\[P_{out} = E_{annual} / 8760\]

\(P_{out}\) is the steady-state electric output (in kW)
\(E_{annual}\) is the annual electric energy generation (in kWh)

References

Blair, N.; Dobos, A.; Freeman, J.; Neises, T.; Wagner, M.; Ferguson, T.; Gilman, P.; Janzou, S. (2014).
System Advisor Model™, SAM™ 2014.1.14: General Description.
NREL/TP-6A20-61019. National Renewable Energy Laboratory. Golden, CO. Accessed May 23, 2025. www.nrel.gov/docs/fy14osti/61019.pdf .

System Advisor Model™ Version 2025.4.16 (SAM™ 2025.4.16).

National Renewable Energy Laboratory. Golden, CO. Accessed May 23, 2025. https://sam.nrel.gov