The System Advisor Model (SAM) is a performance and financial model designed to facilitate decision making for people involved in the renewable energy industry:

SAM's results summary table and graphs.

SAM makes performance predictions and cost of energy estimates for grid-connected power projects based on installation and operating costs and system design parameters that you specify as inputs to the model. Projects can be either on the customer side of the utility meter, buying and selling electricity at retail rates, or on the utility side of the meter, selling electricity at a price negotiated through a power purchase agreement (PPA).

The first step in creating a SAM file is to choose a technology and financing option for your project. SAM automatically populates input variables with a set of default values for the type of project. It is your responsibility as an analyst to review and modify all of the input data as appropriate for each analysis. Next, you provide information about a project's location, the type of equipment in the system, the cost of installing and operating the system, and financial and incentives assumptions.

SAM Models and Databases

SAM represents the cost and performance of renewable energy projects using computer models developed at NREL, Sandia National Laboratories, the University of Wisconsin, and other organizations. Each performance model represents a part of the system, and each financial model represents a project's financial structure. The models require input data to describe the performance characteristics of physical equipment in the system and project costs. SAM's user interface makes it possible for people with no experience developing computer models to build a model of a renewable energy project, and to make cost and performance projections based on model results.

To describe the renewable energy resource and weather conditions at a project location, SAM requires a weather data file. Depending on the kind of system you are modeling, you either choose a weather data file from a list, download one from the Internet, or create the file using your own data.

SAM includes several libraries of performance data and coefficients that describe the characteristics of system components such as photovoltaic modules and inverters, parabolic trough receivers and collectors, wind turbines, and biopower combustion systems. For those components, you simply choose an option from a list, and SAM applies values from the library to the input variables.

SAM can automatically download data and populate input variable values from the following online databases:

• OpenEI U.S. Utility Rate Database for retail electricity rate structures for U.S. utilities
• NREL National Solar Radiation Database for solar resource data and ambient weather conditions.
• NREL WIND Toolkit for wind resource data.
• NREL Biofuels Atlas and DOE Billion Ton Update for biomass resource data.

For the remaining input variables, you either use the default value or change its value. Some examples of input variables are:

• Installation costs including equipment purchases, labor, engineering and other project costs, land costs, and operation and maintenance costs.
• Numbers of modules and inverters, tracking type, derating factors for photovoltaic systems.
• Collector and receiver type, solar multiple, storage capacity, power block capacity for parabolic trough systems.
• Analysis period, real discount rate, inflation rate, tax rates, internal rate of return target or power purchase price for utility financing models.
• Building load and time-of-use retail rates for commercial and residential financing models.
• Tax and cash incentive amounts and rates.

Once you are satisfied with the input variable values, you run simulations, and then examine results. A typical analysis involves running simulations, examining results, revising inputs, and repeating that process until you understand and have confidence in the results.

Results: Tables, Graphs, and Reports

The results data table showing inverter losses for a photovoltaic system.

Performance Models

SAM's performance models make hour-by-hour calculations of a power system's electric output, generating a set of 8,760 hourly values that represent the system's electricity production over a single year. You can explore the system's performance characteristics in detail by viewing tables and graphs of the hourly and monthly performance data, or use performance metrics such as the system's total annual output and capacity factor for more general performance evaluations.

The current version of the SAM includes performance models for the following technologies:

• Photovoltaic systems (flat-plate and concentrating)
• Battery storage model for photovoltaic systems
• Parabolic trough concentrating solar power
• Power tower concentrating solar power (molten salt and direct steam)
• Linear Fresnel concentrating solar power
• Dish-Stirling concentrating solar power
• Conventional thermal
• Solar water heating for residential or commercial buildings
• Wind power (large and small)
• Geothermal power and geothermal co-production
• Biomass power

Time series graph showing hourly results for a 100 MW parabolic trough system with 6 hours of storage.

You can compare different kinds of projects by creating more than one case in a file. For example, you can compare the savings of a residential rooftop solar water heater to those of a photovoltaic system, or for a large utility-scale project, compare the power purchase price that would be required to make a wind, photovoltaic, and concentrating solar power project profitable at a given location. SAM does not model hybrid power systems, so, for example you cannot model a single project that combines wind turbines and photovoltaic modules.

Financial Models

SAM's financial model calculates financial metrics for various kinds of power projects based on a project's cash flows over an analysis period that you specify. The financial model uses the system's electrical output calculated by the performance model to calculate the series of annual cash flows.

SAM includes financial models for the following kinds of projects:

• Residential (retail electricity rates)
• Commercial (retail rates or power purchase agreement)
• Utility-scale (power purchase agreement):
  • Single owner
  • Leveraged partnership flip
  • All equity partnership flip
  • Sale leaseback

Residential and Commercial Projects

Residential and commercial projects are financed through either a loan or cash payment, and recover investment costs through savings from reduced electricity purchases from the electricity service provider. For electricity pricing, SAM can model simple flat buy and sell rates, monthly net metering, or complex rate structures with tiered time-of-use pricing. For these projects, SAM reports the following metrics:

• Levelized cost of energy
• Electricity cost with and without renewable energy system
• Electricity savings
• After-tax net present value
• Payback Period

Power Purchase Agreement (PPA) Projects

Utility and commercial PPA projects are assumed to sell electricity through a power purchase agreement at a fixed price with optional annual escalation and time-of-delivery (TOD) factors. For these projects, SAM calculates:

• Levelized cost of energy
• PPA price (electricity sales price)
• Internal rate of return
• Net present value
• Debt fraction or debt service coverage ratio

SAM can either calculate the internal rate of return based on a power price you specify, or calculate the power price based on the rate of return you specify.

Project Cash Flow

SAM calculates financial metrics from project annual cash flows representing the value of energy savings for projects using retail electricity rates, and the value of revenue from electricity sales for projects selling electricity under a power purchase agreement. For the PPA partnership models, SAM calculates cash flows from the project perspective and from the perspective of each partner.

The first several rows of the cash flow table for a utility-scale project.

The project annual cash flows include:

• Value of electricity sales (or savings) and incentive payments
• Installation costs
• Operating, maintenance, and replacement costs
• Loan principal and interest payments
• Tax benefits and liabilities (accounting for any tax credits for which the project is eligible)
• Incentive payments
• Project and partner's internal rate of return requirements (for PPA projects)

Incentives

The financial model can account for a wide range of incentive payments and tax credits:

• Investment based incentives (IBI)
• Capacity-based incentives (CBI)
• Production-based incentives (PBI)
• Investment tax credits (ITC)
• Production tax credits (PTC)
• Depreciation (MACRS, Straight-line, custom, bonus, etc.)

Analysis Options

In addition to simulating a system's performance over a single year and calculating a project cash flow over a multi-year period, SAM's analysis options make it possible to conduct studies involving multiple simulations, linking SAM inputs to a Microsoft Excel workbook, and working with custom simulation modules. The following options are for analyses that investigate impacts of variations and uncertainty in assumptions about weather, performance, cost, and financial parameters on model results:

The report generator exports a PDF file with a summary of the main inputs and results from a SAM analysis case..

• Parametric Analysis: Assign multiple values to input variables to create graphs and tables showing the value of output metrics for each value of the input variable. Useful for optimization and exploring relationships between input variables and results.
• Sensitivity Analysis: Create tornado graphs by specifying a range of values for input variables as a percentage.
• Stochastic: Assign multiple values to input variables using parameters for statisitical distributions.
• P50/P90: For locations with weather data available for many years, calculate the probability that the system's total annual output will exceed a certain value.

Software Development History and Users

SAM, originally called the "Solar Advisor Model" was developed by the National Renewable Energy Laboratory in collaboration with Sandia National Laboratories in 2005, and at first used internally by the U.S. Department of Energy's Solar Energy Technologies Program for systems-based analysis of solar technology improvement opportunities within the program. The first public version was released in August 2007 as Version 1, making it possible for solar energy professionals to analyze photovoltaic systems and concentrating solar power parabolic trough systems in the same modeling platform using consistent financial assumptions. Since 2007, two new versions have been released each year, adding new technologies and financing options. In 2010, the name changed to "System Advisor Model" to reflect the addition of non-solar technologies.

The DOE, NREL, and Sandia continue to use the model for program planning and grant programs. Since the first public release, over 35,000 people representing manufacturers, project developers, academic researchers, and policy makers have downloaded the software. Manufacturers are using the model to evaluate the impact of efficiency improvements or cost reductions in their products on the cost of energy from installed systems. Project developers use SAM to evaluate different system configurations to maximize earnings from electricity sales. Policy makers and designers use the model to experiment with different incentive structures.

Downloading SAM and User Support

SAM runs on Windows, OS X, and Linux. It requires about 500 MB of storage space on your computer. SAM is available for free download.

SAM's help system includes detailed descriptions of the user interface, modeling options, and results.

The following resources are available for learning to use SAM and for getting help with your analyses:

• Help system: Press the F1 key in Windows or Command-? in Mac OS from any input or results page in SAM to view the Help topic for that page.
• User support forum
• Documentation, videos, and training schedule on the SAM website Learning page

You can email the SAM support team by submitting a message on the Contact Us page.

Model Structure

SAM consists of a user interface, calculation engine, and programming interface. The user interface is the part of SAM that you see, and provides access to input variables and simulation controls, and displays tables and graphs of results. SAM's calculation engine performs a time-step-by-time-step simulation of a power system's performance, and a set of annual financial calculations to generate a project cash flow and financial metrics. The programming interface allows external programs to interact with SAM.

The user interface performs three basic functions:

• Provide access to input variables, which are organized into input pages. The input variables describe the physical characteristics of a system, and the cost and financial assumptions for a project.
• Allow you to control how SAM runs simulations. You can run a basic simulation, or more advanced simulations for optimization and sensitivity studies.
• Provide access to output variables in tables and graphs on the Results page, and in files that you can access in a spreadsheet program or graphical data viewer.

Simulation Engine

Each renewable energy technology in SAM has a corresponding performance model that performs calculations specific to the technology. Similarly, each financing option in SAM is also associated with a particular financial model with its own set of inputs and outputs. The financial models are as independent as possible from the performance models to allow for consistency in financial calculations across the different technologies.

A performance simulation consists of a series of many calculations to emulate the performance of the system over a one year period in time steps of one hour for most simulations, and shorter time steps for some technologies.

A typical simulation run consists of the following steps:

1. After starting SAM, you select a combination of technology and financing options for a case in the user interface.
2. Behind the scenes, SAM chooses the proper set of simulation and financial models.
3. You specify values of input variables in the user interface. Each variable has a default value, so it is not necessary to specify a value for every variable.
4. When you click the Simulate button, SAM runs the simulation and financial models. For advanced analyses, you can configure simulations for optimization or sensitivity analyses before running simulations.
5. SAM displays graphs and tables of results in the user interface's Results page.