The complexity and resolution required to model the modern power system is rapidly increasing. The widespread introduction of resources such as wind and solar power motivates the need to study both the impact of uncertainty in production and specific deployment scenarios. Distributed energy resources, demand response, new bulk power generation, inter-sectoral dependencies, and evolving consumer preferences further contribute to the need to develop new production cost modeling (PCM) capabilities to address growing uncertainty and system complexity.
Many power system planners and reliability coordinators have indicated that in order to plan for the rapidly changing electricity system, they must be able to simulate a broad range of highly detailed power system scenarios. Traditionally, they have been forced to choose between conflicting goals when performing PCM-based analyses: model fidelity, the ability to address uncertainty, and execution time. Reducing model resolution and/or ignoring uncertainty in turn detrimentally impact the relevancy of the simulations, but decreases execution time. Similarly, long execution times limit the number of scenarios that planners and reliability coordinators can analyze.
This project is dramatically reducing the time required by industry to analyze future power system scenarios through PCM, while considering higher-fidelity representations of the underlying systems. By developing and leveraging advanced computational tools and delivering the tools and expertise through industry outreach, the project team is introducing significant acceleration of existing PCM simulations as well as demonstrating and deploying the tools to address uncertainty associated with high renewables penetrations.