Scalable Power System Modeling and Analaysis
2021-07-29 , Red

The Scalable Integrated Infrastructure Planning (SIIP) initiative at NREL has developed a set of high-performance power system simulation capabilities with PowerSystems.jl and PowerSimulations.jl. This talk will demonstrate these capabilities with interactive examples using large realistic datasets, and provide theoretical background for software design choices.


This talk will provide practical modeling examples and theoretical justification for design choices made in the Scalable Integrated Infrastructure Planning (SIIP) Initiative at the National Renewable Energy Lab (NREL). We will demonstrate the suite of power systems focused packages – SIIP::Power to perform large-scale power systems modeling and analysis activities. In particular, this talk will highlight:
- InfrastructureSystems.jl: for enabling large-scale infrastructure system data set management and access
- PowerSystems.jl: for specifying quasi-static and dynamic power systems data
- PowerSimulations.jl: for enabling optimization based power systems modeling, including production cost modeling and optimal power flow using PowerModels.jl
- PowerGraphics.jl: for visualizations of results generated by PowerSystems.jl and PowerSimulations.jl

Examples will focus on standard modeling practice and highlight opportunities to customize and extend capabilities to meet individual needs.

Clayton Barrows is a member of the Forecasting and Modeling Group at the National Renewable Energy Laboratory. His research focuses on improving the technical and economic efficiency of energy systems through advanced computation and analysis. At NREL, Clayton leads a team in developing and utilizing energy and infrastructure systems models to gain new insights into pathways towards system modernization. In his research, Clayton draws upon deep experience in applying the tools of network science and optimization to improve the fidelity and scalability of infrastructure systems models. He has applied these techniques to inform policy in studies and applications around the world.