Distributionally Robust Optimization for a Resilient Transmission Grid During Geomagnetic Disturbances

TL;DR

This paper introduces a distributionally robust optimization approach to enhance the resilience of power grids against geomagnetic disturbances, accounting for uncertainties in GMD predictions and system controls.

Contribution

It develops a novel two-stage DR optimization model that captures GMD uncertainties and applies advanced solution methods for resilient power system operation.

Findings

Effective handling of GMD prediction errors

Improved system resilience through robust control strategies

Demonstrated on the Epri21 system

Abstract

In recent years, there have been increasing concerns about the impacts of geomagnetic disturbances (GMDs) on electrical power systems. Geomagnetically-induced currents (GICs) can saturate transformers, induce hot-spot heating and increase reactive power losses. Unpredictable GMDs caused by solar storms can significantly increase the risk of transformer failure. In this paper, we develop a two-stage, distributionally robust (DR) optimization formulation that models uncertain GMDs and mitigates the effects of GICs on power systems through existing system controls (e.g., line switching, generator re-dispatch, and load shedding). This model assumes an ambiguity set of probability distributions for induced geo-electric fields which capture uncertain magnitudes and orientations of a GMD event. We employ state-of-the-art linear relaxation methods and reformulate the problem as a two-stage DR model. We use this formulation to develop a decomposition framework for solving the problem. We demonstrate the approach on the modified Epri21 system and show that the DR optimization method effectively handles prediction errors of GMD events.