Geomagnetic Storm and its Impact on Time-Dependent Transformer Thermal Response in Large Power Systems

Abstract

Geomagnetically induced currents (GICs) in power systems are a potential source of introduc-ing DC in transformers, resulting in undesirable occurrences of additional harmonics and higher temperatures. The purpose of this thesis is to analyze the behavior of transformers in a large-scale power system under the influence of GMD. Looking at the bigger picture, the idea is to model the risk on a synthetic grid in order to improve the system’s resilience. By modeling severe GMD events from various derivations of NERC Benchmark Event, it gives us a visualization of how big of a GMD event is needed to be concerned about the stability of the power system.

This thesis reviews the methodology and results of the case studies that were performed on the transformer fleet of a 2000-bus synthetic grid on the geographic footprint of Texas. The thermal assessment technique identifies the transformers with potential thermal impacts using a first-order hotspot calculation method for the structural parts of the power transformer. Firstly, a thermal model for approximating the hotspot temperature rise is developed. The total hotspot temperature obtained from the thermal model is used to determine the transformers that violate the condition-based GIC susceptibility categories depending on how long the transformers have been in service. The analysis is undertaken by modeling severe GMD events—NERC benchmark event and its derivatives—to assess how the transient hotspot behavior of a power transformer is related to var-ious environmental conditions, such as electric field magnitude and direction, transformer neutral current, and storm duration.

This thesis also aims to present a methodology for creating severe synthetic GMD storms with the primary goal of testing the resiliency of the power system. To accomplish this, the time-series fragments of Electric field data extracted at random from the NERC benchmark event undergo spatial and temporal transformation. The resultant ’modified’ fragments are concatenated to form a synthetic temporal E-field dataset. Many iterations of this process can result in a range of synthetic storms that vary in duration, intensity, and direction. The extremity of a synthetic GMD storm is then investigated through the lens of transformer thermal assessment on the 2000-bus synthetic case. This can aid in gaining heightened system awareness in the possible event of an extreme GMD event.

In conclusion, this thesis can facilitate in narrowing the focus to the susceptible components of the bulk-power system during an extreme GMD event so that GIC mitigation strategies could be devised accordingly to maintain a resilient power grid.