| Grid stability
and inertia measurement to support the country’s transition to carbon neutrality by 2050. In Taiwan, Taipower’s deployment reveals that 34% of system inertia is residual (ie, inherent or ‘embedded’ in the system) and was previously unaccounted for. This insight informs renewable integration planning and enables the world’s first use of a battery energy storage system as the modulator for active inertia measurement. In Australia, AEMO, with validation from the University of Melbourne, documented operational and planning benefits from real time inertia measurement in a market with rising renewable penetration. The study revealed that on average there is approximately 38% more inertia in the system than AEMO was able to estimate. These examples show a common pattern: operators use real time measurement to validate models, refine stability limits, and reduce precautionary actions, cutting costs and accelerating renewable integration.
Why local dynamics matter for system stability
Stability is no longer just a transmission-level concern. Increasingly, risks originate at the distribution level, driven by data centres, electronic loads, and distributed energy resources. A disturbance at a single node, such as oscillations from inverter-based resources or sudden demand changes from large loads, can propagate through the network and amplify into wider instability. Local variations in inertia and system strength influence how the entire grid responds to frequency and voltage changes. When these parameters fluctuate unpredictably, operators risk misjudging stability margins. As mentioned previously, Reactive Technologies’ GridMetrix®
GridMetrix® heat map of the UK transmission grid. Image: Reactive Technologies
system. Addressing these issues early helps operators avoid expensive grid upgrades and maintain service quality.
From measurement to prediction: the next frontier
platform provides an integrated view of dynamic operability, measuring inertia, system strength, and oscillations across the grid. Looking ahead, this capability is expanding to include power quality indicators such as flicker and harmonics, ensuring operators can manage emerging challenges at every level of the network. Real-time measurement at the local level provides the high-resolution data needed to detect emerging risks early, prevent cascading effects, and maintain security across the whole
Looking ahead, the next frontier is prediction rather than reaction. Real-time measurement provides the foundation, but operators increasingly need to anticipate stability risks before they emerge. Combining high-definition grid measurement with forecasting and AI-driven analytics enables this shift. Machine learning models use historical and live data to predict inertia, system strength, and oscillatory risk under changing conditions such as weather, dispatch schedules, and grid topology.
High-resolution performance data is critical to this process. It ensures predictive models are anchored in accurate, granular observations, allowing operators to trust forecasts and act decisively. These insights enable earlier scheduling of the right services, validating their impact in real time, and reducing reliance on precautionary actions.
Planning and operations are converging. The same data that informs control-room decisions
will increasingly guide outage planning and long- term reinforcement studies. By aligning predictive analytics with established planning processes, we can shorten the loop between observed risk, operational mitigation, and structural investment, unlocking more grid capacity while ensuring a stable and resilient system.
Delivering a stable, low carbon grid Grid stability and power quality are twin pillars of a reliable, low-carbon system. Global grids are not in crisis; they are transitioning to new conditions shaped by renewable generation, emerging load types, and tighter security margins that require high resolution measurement strategies. Operators require tools that reduce uncertainty and provide clear visibility of dynamic behaviour. Real time measurement of inertia, system strength, and oscillations offer that visibility. It transforms uncertainty into actionable information, enabling operators to run stable grids closer to limits without compromising security while providing critical insights to planning teams as they design the future grid. If we are to achieve our ambitious goals for the future, then real-time stability measurement is one of the foundational elements it will be built on.
Purpose built system strength modulator being installed to actively measure short circuit level. Photo: Reactive Technologies
Dongshan battery energy storage system providing signals (modulation) for Taipower, Taiwan. Photo: Taipower/Reactive Technologies
www.modernpowersystems.com | November/December 2025 | 19
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