Online Security Assessment of Low-Inertia Power Systems: A Real-Time Frequency Stability Tool for the Australian South-West Interconnected System

TL;DR

This paper introduces a real-time frequency stability tool for low-inertia power systems, enabling operators to predict frequency deviations accurately and ensure sufficient reserves, crucial for preventing blackouts in renewable-heavy grids.

Contribution

The paper develops and operationalizes a real-time frequency stability tool tailored for low-inertia power systems, with simplified generator modeling and calibration against actual data.

Findings

The tool accurately predicts frequency trajectories after contingencies.

Calibration against historical data improves prediction accuracy.

Implementation enhances system reliability in low-inertia environments.

Abstract

In small/medium-sized isolated power networks with low rotational inertia and high penetration of renewables, generation/load contingency events may cause large frequency excursions, potentially leading to cascading failures and even blackouts. Therefore, it is crucial for system operators to be able to monitor the state of the network in real-time and predict the maximum possible frequency deviations at all times. This paper presents a real-time frequency stability (RTFS) tool developed by the Australian Energy Market Operator (AEMO) and operationalized in the control room for the South West Interconnected System (SWIS) to ensure that the available spinning reserve is sufficient and fast enough to arrest frequency excursions under any conditions, and particularly low-inertia ones. To reduce the computational burden and complexity of the different turbine-governor models, a simple first-order lag function with two adjustable variables has been used for each of the generator. These adjustable parameters, along with other key model parameters such as load damping and inertia, have been calibrated against actual frequency response using high-speed fault recorder data from historical events. As demonstrated in several case studies, the real-time tool has proven to be accurate at predicting the trajectory of system frequency after credible contingencies, thus suggesting that similar implementations could be carried out elsewhere while power systems worldwide progress towards lower inertia.