PRAS The Probabilistic Resource Adequacy Suite

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Name

PRAS The Probabilistic Resource Adequacy Suite

Screenshots

No response

Focus Topic

PRAS provided representation of a power system to a probabilistic description of operational outcomes of interest, using a particular choice of operations simulation, and allows to study power system resource adequacy

Primary Purpose

The Probabilistic Resource Adequacy Suite (PRAS) is a collection of tools for bulk power system resource adequacy analysis and capacity credit calculation.

Description

The Probabilistic Resource Adequacy Suite, or PRAS, is a software package for studying power system resource adequacy. 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.

Mathematical Description

PRAS provided representation of a power system to a probabilistic description of operational outcomes of interest, using a particular choice of operations simulation. The simulation methods offered support everything from classical convolution-based analytical techniques through to high-performance sequential Monte Carlo methods supporting multi-region composite reliability assessment, including simulation of energy-limited resources such as storage.

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 As illustrated in Figure 1, 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 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.

Website

https://nrel.github.io/PRAS/

Documentation

https://www.nrel.gov/docs/fy21osti/79698.pdf

Source

https://nrel.github.io/PRAS/installation

Year

2021

Institution

NREL

Funding Source

U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office and Solar Energy Technologies Office

Publications

1

Publication List

1. Stephen, G. (2021). Probabilistic resource adequacy suite (PRAS) v0. 6 model documentation (No. NREL/TP-5C00-79698). National Renewable Energy Lab.(NREL), Golden, CO (United States).

Use Cases

No response

Infrastructure Sector

• Atmospheric dispersion
• Agriculture
• Biomass
• Buildings
• Communications
• Cooling
• Ecosystems
• Electric
• District heating
• Forestry
• Health
• Hydrogen
• Individual heating
• Land use
• Liquid fuels
• Natural Gas
• Transportation
• Water

Represented Behavior

• Earth Systems
• Employment
• Built Infrastructure
• Financial
• Macro-economy
• Micro-economy
• Policy
• Social

Modeling Paradigm

• Analytics
• Data
• Discrete Simulation
• Dynamic Simulation
• Equilibrium
• Engineering/Design
• Optimization
• Visualization

Capabilities

1. Analysing the resource adequacy of a bulk power system
2. Capacity Credit Calculation
3. Equivalent Firm Capacity (EFC)
4. Effective Load Carrying Capability (ELCC)

Programming Language

• C – ISO/IEC 9899
• C++ (C plus plus) – ISO/IEC 14882
• C# (C sharp) – ISO/IEC 23270
• Delphi
• GAMS (General Algebraic Modeling System)
• Go
• Haskell
• Java
• JavaScript(Scripting language)
• Julia
• Kotlin
• LabVIEW
• Lua
• MATLAB
• Modelica
• Nim
• Object Pascal
• Octave
• Pascal Script
• Python
• R
• Rust
• Simulink
• Swift (Apple programming language)
• WebAssembly
• Zig

Required Dependencies

No response

What is the software tool's license?

MIT License (MIT)

Operating System Support

• Windows
• Mac OSX
• Linux
• iOS
• Android

User Interface

• Programmatic
• Command line
• Web based
• Graphical user
• Menu driven
• Form based
• Natural language

Parallel Computing Paradigm

• Multi-threaded computing
• Multi-core computing
• Distributed computing
• Cluster computing
• Massively parallel computing
• Grid computing
• Reconfigurable computing with field-programmable gate arrays (FPGA)
• General-purpose computing on graphics processing units
• Application-specific integrated circuits
• Vector processors

What is the highest temporal resolution supported by the tool?

Years

What is the typical temporal resolution supported by the tool?

None

What is the largest temporal scope supported by the tool?

Years

What is the typical temporal scope supported by the tool?

None

What is the highest spatial resolution supported by the tool?

Region

What is the typical spatial resolution supported by the tool?

None

What is the largest spatial scope supported by the tool?

Region

What is the typical spatial scope supported by the tool?

None

Input Data Format

pras, jl

Input Data Description

No response

Output Data Format

jl

Output Data Description

No response

Contact Details

gord.stephen@nrel.gov

Interface, Integration, and Linkage

https://github.com/NREL/PRAS/issues