Photovoltaic Reliability Performance Model (PV-RPM v2.0 Beta)

What is it:

Sandia National Laboratories (SNL) and National Renewable Energy Laboratory (NREL) have partnered to bring you this public Beta version of the PV Reliability Performance Model Version 2.0 (PV-RPM v2.0) that can be run from the LK scripting environment within SAM. This new feature is provided in SAM to allow users with reliability data the ability to develop and run scenarios where PV performance and costs are impacted from components that can fail stochastically.

The PV-RPM model was initially developed in 2010 by SNL as a proof-of-concept for better simulating the uncertainty when components experience faults or failures in a fielded PV system. As the events occur randomly, they can be represented as a probability distribution with specific parameters to define the severity of the event and when it may occur over a specific time-frame. Repairs or replacements are also represented with probability distributions, where the component remains in a failed state until the repair distribution is sampled and results in the component being returned to an operating state. In 2016, SNL partnered with NREL to move the PV-RPM algorithms from the proof-of-concept platform into SAM, via the LK scripting environment. Doing this allows users to see how the code works and gives them the ability to modify the code for their own purposes.

The code is available in SAM through an open-source license, with copyright asserted from the DOE Solar Energy Technologies Office on 12/16/2016. The copyright language can be found within each of the SAM LK script files..

To use it:

Please download the zip file (ZIP 2.7 MB) and read the included user manual for instructions on how to use PV-RPM v2.0 Beta.

Important notes:

  • This feature runs on the Windows platform ONLY
  • This feature is not supported by the SAM Support email address, please use the email address below for questions and problems!

Feedback, comments, and questions:

This model and instructions are still in a Beta release, so you should expect imperfections, bugs, and room for improvement. Please email Geoff Klise, the project lead at Sandia National Laboratories, with any questions, comments, bug reports, or suggestions. We value your feedback!

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