As a longtime proponent of open source solar photovoltaic development, I am happy that the U.S. National Renewable Energy Lab (NREL) has shared all the source code for System Advisor Model (SAM), its most powerful renewable energy economic analysis software.
SAM is now SAM Open Source. It is a performance and financial model designed to help make decisions about renewable energy. This is perfect timing, as the costs of solar have dropped so far that the levelized cost of electricity for solar power is less than what you are probably paying for electricity from your utility.
Simply speaking: For most people in the United States, it is now profitable to install solar photovoltaic (PV) systems at their homes or businesses. As a single example among millions, my non-optimal, partially shaded garage covered with solar panels is earning a double-digit return on investment (ROI) in the not-so-sunny and very snowy upper peninsula of northern Michigan. If your investment income isn't averaging post-tax double digits and you live anywhere in the United States, it is worth taking a quick peek to see whether you, too, could turn a tidy profit with solar.
You can use PVWatts, a free, quick, and easy tool supported by NREL that can help estimate your PV energy production (and ROI); however, if you really want to dive into the financial analysis—particularly for large, complex projects—SAM is the tool for you. SAM makes solid, bankable performance predictions and cost-of-energy estimates for grid-connected power projects from a long list of renewable energy sources, including:
- PV systems (flat-plate and concentrating)
- Battery storage model for PV 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
- Process heat parabolic trough and linear direct steam
- A simple "generic model" for conventional thermal
- Solar water heating for residential or commercial buildings
- Wind power (large and small)
- Geothermal power and geothermal co-production
- Biomass power
SAM is populated by reasonable default values for all major variables that you can change for your specific circumstances (for example installation and operating costs and system design parameters that you can specify as inputs to the model). It automatically pulls data that you need, like weather, from other databases. 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 choices will depend on your project and where it is in the country.
Considering the complexity of these calculations, SAM does a good job of making the analysis accessible, but there is a modest learning curve to using it correctly. Lots of help is available, such as sample case studies and a fairly comprehensive set of recorded webinars. Overall, in my opinion as an expert in the field (my PhD is in low-cost photovoltaics), SAM is a nice piece of software. It has been validated and is reliable as long as you are careful about using realistic input parameters. I have been using SAM with my graduate students to analyze potential novel solar energy systems for a long time.
Why open source matters
SAM has been available for free for years, but open sourcing it is still a big deal. NREL says the benefits of SAM Open Source include:
- Transparency: Explore the source code to find equations and algorithms so you can see exactly how the models work.
- Flexibility: Change the code and build your own versions of SAM to add your own features and capabilities.
- Collaboration: Contribute new models, fix bugs, or work with NREL to implement new features that can be added to the NREL versions of SAM.
These and all the normal benefits of open source are good and logical reasons for using SAM Open Source, but let me provide one more—having access to the code ensures you will not get burned if SAM became hobbled, were discontinued, lost support, or was pulled for any, unknown reason by the government that funded it.
Our tiny, single-gate local airport, for example, has the surface area to conservatively provide power for 15,000 homes (half of the county's population) while making millions of dollars. There is an enormous opportunity for all the other small, rural airports to cash in as well. To ensure that the solar panels do not in any way interfere with air traffic, these airports would need to follow the rules outlined in our paper and those set out by the Federal Aviation Administration (FAA). Ideally, they would use a program to assist in the array design to eliminate any glare risks. Such a program—the Solar Glare Hazard Analysis Tool—has already been developed by Sandia National Labs with government tax dollars; however, in 2016, Sandia disabled the (SGHAT) web application (versions 1 and 2) it had previously made available on its website.
For reasons not known to the current licensing executives at Sandia, the software is now available only for commercial licensing, by subscription, and from only one vendor. If we assume that each airport in the U.S. would want access to the Enterprise version to enable the full optimization of PV arrays as well as enhanced flight paths over a year of planning, the cost would be more than US $24.3 million for something that was developed with tax dollars. This cost barrier could, in part, explain why such a small percentage of airports in the United States have moved to solar, despite the overwhelming economic advantages seen by large-scale solar PV systems.
Given this experience, I hope that other government labs and agencies follow the leadership and good judgment displayed by NREL and decide to open source their best software for the benefit of the American public.