ALM (Advanced Load Modeling)

Load characteristics are changing rapidly due to emerging climate, demographic, and technology trends, such as the increase in electrification in the U.S. energy grid which can have a significant impact on load shapes. These changes pose challenges for supply-side planning. Planning models need to be updated annually with new data, assumptions, and strategies for assuring system adequacy.

GISMo’s Advanced Load Modeling project aims at enhancing the accuracy and reliability of load modeling to improve power system planning and ensure the reliability and efficiency of transmission and distribution networks. Since 2018, the GISMo team has been supporting the NERC Load Modeling Task Force (LMFT) in this effort by developing software tools and analytical methods enhancing the quality of load model data, and supplementing existing data-driven approaches with physics-based load composition modeling tools. 

The current work in ALM is focused on quantifying the electrification potential across the country and forecasting the new load shapes to update regional peak loads emerging from decarbonization and electrification. These crucial updates to load models prepare us to better manage the increasing load on the power grid as electrification increases over the next few decades. Additionally, ALM aims to understand load behavior in the presence of extreme weather, predict consumer behavior changes, and study transportation loads as they grow rapidly with the growth of electric vehicle adoption rates. 

The tools and methodologies developed in this project will pave the way to accurate long term load modeling and load characteristics forecasting necessary to ensure the future reliability and resiliency of the power grid.

Project lead: David Chassin