PRAS

The Probabilistic Resource Adequacy Suite (PRAS) provides an open-source, research-oriented collection of tools for analysing the resource adequacy of a bulk power system. It allows the user to simulate power system operations under a wide range of operating conditions in order to study the risk of failing to meet demand (due to a lack of supply or deliverability), and identify the time periods and regions in which that risk occurs. It offers high-performance sequential Monte Carlo methods supporting multi-region composite reliability assessment, including simulation of energy-limited resources such as storage.

PRAS is developed and maintained at the US National Renewable Energy Laboratory (NREL).

To get started on using PRAS, see the installation and quick start pages.

Basic usage

PRAS maps a provided representation of a power system to a probabilistic description of operational outcomes of interest, using a particular choice of operations simulation. The input system representation is called a "system model", the choice of operational representation is referred to as a "simulation specification", and different types of operating outcomes of interest are described by "result specifications".

PRAS model structure and corresponding assessment function arguments

PRAS is written in the Julia programming language, and is controlled through the use of Julia scripts. The three components of a PRAS resource adequacy assessment (a system model, a simulation specification, and result specifications) map directly to the Julia function arguments required to launch a PRAS run. A typical resource adequacy assessment with PRAS involves creating or loading a system model, then invoking PRAS' assess function to perform the analysis:

using PRAS

sys = SystemModel("filepath/to/mysystem.pras")

shortfallresult, flowresult =
    assess(sys, SequentialMonteCarlo(), Shortfall(), Flow())

eue, lole = EUE(shortfallresult), LOLE(shortfallresult)