The growing contribution of renewable energy sources and energy storage systems to the US. power grid, combined with a gradual transition away from traditional rotating generators, has resulted in new grid stability and behavior patterns. Traditionally, power systems were dominated by synchronous machines in which a crucial source of grid stability came from physical rotations that behaved according to the laws of physics. Emerging power systems increasingly rely on renewable energy sources and inverter-based generation where stability is maintained not through mechanical processes, but through logic and electronic controls.

New open-source simulation tools and a computational approach have been developed by researchers from the University of California Berkeley and the U.S. National Renewable Energy Laboratory to reflect modern grid structure characteristics more accurately. The computational framework is based on the Julia programming language to support the development of open-source tools that provide consistent and high-performance data models for utility-scale power systems. The resulting Scalable Integrated Infrastructure Planning (SIIP) modeling framework incorporates new solution algorithms, advanced data analytics and scalable high-performance computing.

Different modeling packages within SIIP include a reusable and customizable data model that is generic to the implementation details of the mathematical models and is applicable to multiple simulation strategies. Additional capabilities enable steady-state power system modeling activities, including production cost modeling, unit commitment, economic dispatch, automatic generation control simulations and optimal power flow. Power system dynamics can be simulated by providing access to an extensive model library and to several numerical integrators in Julia.

A research paper detailing the development and use of SIIP is published in IEEE Electrification.