Polynomial Fitting and Analysis of Geomagnetic Disturbance Impacts

Geomagnetic disturbances (GMDs) are a threat to power systems with the potential to cause large impacts on grids around the world through the creation of geomagnetically induced currents (GICs). Modeling GMDs with detailed power system impact analysis is crucial, as GICs cause transformers to overheat and saturate, causing reactive power losses and lower voltages. The scale of impact is related to the severity of the storm. While the ability to systematically study the impacts of GICs on power systems has greatly improved over the past decade, it remains a challenge to predict these storms and to study and prepare for impacts of future storms. Hence, the goal of this paper is to create a mathematical model of GMD storms to predict how stronger storms will impact the grid in the future. To obtain this model, polynomial regression is applied to magnetic field data to obtain an equation. The equation models the general shape of GMDs, and it allows for alterations based on the location, time, and strength of each GMD. Analyzing these features helps to understand the effect they have on GMDs and to generate better models. The models in this work generate the general shape of past GMD storms, however there are variations by location, adding challenges for analysis.