Real-Time Stochastic Assessment of Dynamic N-1 Grid Contingencies

TL;DR

This paper presents a real-time framework for assessing dynamic N-1 grid contingencies, enabling rapid risk evaluation of transient faults and overloads in power systems.

Contribution

It introduces a scalable fault evaluation algorithm, a dynamic overload indicator, and a risk estimation method for real-time grid security assessment.

Findings

Effective screening of dynamic contingencies demonstrated on Israeli grid.

Linear-scaling algorithm enables rapid impact assessment.

Risk estimation accurately identifies low probability high-impact events.

Abstract

Power system operators need tools for rapid, real-time counterfactual assessments of grid security under fast-changing conditions. Traditional N-1 contingency analysis lacks dynamic evaluation, especially of frequency swings from common faults. This paper introduces a real-time dashboard framework to screen dynamic contingencies. It assumes: (a) the grid starts in a balanced state; (b) faults can occur randomly on any transmission line, temporarily de-energizing and then reconnecting it within about one second; and (c) contingencies are flagged if post-fault transients cause line flows to exceed safety thresholds. The key contributions are: (1) Overload Indicator: a system-wide metric quantifying integrated N-1 dynamic risk from a given state; (2) Scalable Fault Evaluation Algorithm: a linear-scaling method to assess dynamic fault impacts without brute-force simulations; and (3) Risk Estimation: a Cross Entropy Adaptive Importance Sampling method estimating the likelihood of low probability by high risk events, e.g. associated with potential transformer over-current. We demonstrate the framework on the Israeli transmission power grid (IG).