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.
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
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
[X] Biomass
[X] Buildings
[ ] Communications
[X] Cooling
[ ] Ecosystems
[X] Electric
[X] District heating
[ ] Forestry
[ ] Health
[X] Hydrogen
[X] Individual heating
[ ] Land use
[X] Liquid fuels
[X] Natural Gas
[X] Transportation
[X] Water
Represented Behavior
[ ] Earth Systems
[ ] Employment
[X] Built Infrastructure
[ ] Financial
[ ] Macro-economy
[ ] Micro-economy
[ ] Policy
[ ] Social
Modeling Paradigm
[ ] Analytics
[ ] Data
[ ] Discrete Simulation
[ ] Dynamic Simulation
[ ] Equilibrium
[X] Engineering/Design
[X] Optimization
[ ] Visualization
Capabilities
Analysing the resource adequacy of a bulk power system
Capacity Credit Calculation
Equivalent Firm Capacity (EFC)
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)
[X] 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
[X] Windows
[X] Mac OSX
[X] Linux
[ ] iOS
[ ] Android
User Interface
[X] Programmatic
[ ] Command line
[ ] Web based
[X] 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?
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
Use Cases
No response
Infrastructure Sector
Represented Behavior
Modeling Paradigm
Capabilities
Programming Language
Required Dependencies
No response
What is the software tool's license?
MIT License (MIT)
Operating System Support
User Interface
Parallel Computing Paradigm
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