NREL-PySAM ========== NREL-PySAM is a wrapper for the National Renewable Energy Laboratory's `System Advisor Model `_ (SAM), a simulator for renewable energy, not to be confused with `pysam `_, which is for reading sequence alignment files often used in genetics. SAM is a performance and financial model designed to facilitate decision making for people involved in the renewable energy industry: - Project managers and engineers - Policy analysts - Technology developers - Researchers `SAM `_ is open-source. PySAM provides a native Python interface for the models found in SAM Simulation Core, (`SSC `_). Getting Started ------------------------------------------ Learn how to install the package from PyPi or the Conda registry. Write your first PySAM script and run a renewable energy power system simulation in a few steps following some examples. Or, take a look at how cases from the SAM Desktop application can be imported into PySAM. * **First steps**: :doc:`Installation and Import ` * **Creating models** :doc:`Examples ` | :doc:`Importing a case from SAM ` .. toctree:: :maxdepth: 2 :hidden: :caption: Getting Started /GettingStarted /Examples /Import Models and Tools ------------------------------------------ PySAM offers all the technology and financial models available in SAM as separate modules. Learn about individual models and how to chain models together to create a configuration. PySAM includes tools that provide design and resource functionality. * **Technology and Financial Models**: :doc:`Available models ` | :doc:`Configurations ` | * **Tools**: :doc:`Design & Resource Tools ` | :doc:`PySSC Wrapper ` .. toctree:: :maxdepth: 2 :hidden: :caption: Models and Tools Models Configs Tools Version 2.0 and Upgrading from Older Versions ------------------------------------------ Between major version changes, in addition to new features, modules and bug fixes, the group to which a variable belongs may change. The groups should stabilize after the initial releases. Please see :doc:`Version` for more details. .. toctree:: :maxdepth: 2 :hidden: :caption: About Read the Docs PySSC