Load-Altering Attacks Against Power Grids: A Case Study Using the GB-36 Bus System Open Dataset

TL;DR

This study analyzes the impact of load-altering cyber attacks on the UK power grid using real-world data, assessing vulnerabilities and mitigation strategies involving Battery Energy Storage Systems through detailed simulations.

Contribution

It provides a practical case study of load-altering attacks on a real transmission network, evaluating thresholds and mitigation methods with open-source data and realistic simulations.

Findings

LAA severity thresholds for grid stability identified

BESS can effectively mitigate LAA impacts

Attack location and timing significantly influence system response

Abstract

The growing digitalization and the rapid adoption of high-powered Internet-of-Things (IoT)-enabled devices (e.g., EV charging stations) have increased the vulnerability of power grids to cyber threats. In particular, the so-called Load Altering Attacks (LAAs) can trigger rapid frequency fluctuations and potentially destabilize the power grid. This paper aims to bridge the gap between academic research and practical application by using open-source datasets released by grid operators. It investigates various LAA scenarios on a real-world transmission network, namely the Great Britain (GB)-36 Zone model released by the UK's National Electricity System Operator (NESO). It evaluates the threshold of LAA severity that the grid can tolerate before triggering cascading effects. Additionally, it explores how Battery Energy Storage Systems (BESS) based fast frequency response services can mitigate or prevent such impacts. Simulations are conducted using DIgSILENT PowerFactory to ensure realistic system representation. The analysis provides several useful insights to grid operators on the LAA impact, such as the influence of the relative locations of BESS and LAA, as well as how delays in attack execution can influence the overall system response.