Taipower Implements Real-Time Grid Inertia System to Support Renewables
Taipower scales real-time inertia tracking and energy storage to improve grid stability under higher renewables and AI-era loads.
Taiwan Power Company (Taipower) has achieved a regional milestone in grid management by deploying real-time inertia measurement technology across its national transmission network. The innovation is the result of a collaboration with UK-based Reactive Technologies, whose GridMetrix® platform enables operators to calculate system inertia in real time.
Inertia, a property traditionally supplied by spinning generators, helps maintain grid frequency during fluctuations. As more renewables like wind and solar replace conventional thermal generation, system inertia declines, posing a risk to grid stability. The ability to measure and eventually forecast inertia in real time is essential for operating modern, renewable-heavy power systems.
A distinctive element of the project is the use of battery energy storage systems (BESS) to actively modulate grid signals for inertia measurement. According to Taipower’s Chief Digital Officer, Dr. Wu Chin-Chung, this makes Taiwan one of the few jurisdictions globally to integrate BESS with system inertia visibility tools at a market-wide scale.
Initial assessments found that Taiwan’s grid retains more residual inertia than previously estimated, offering operators more headroom for solar and wind capacity additions. The next phase of the project includes the deployment of an AI-powered forecasting engine to anticipate changes in inertia based on generation and load forecasts.
The rollout is part of Taiwan’s broader strategy to modernize its grid infrastructure in support of the government’s 2050 net-zero target. Taipower’s investment in smart grid capabilities reflects a growing regional emphasis on making power systems more responsive to the operational challenges of high renewables and compute-intensive loads such as AI data centers.
This development comes as other utilities in Asia explore similar strategies for real-time grid visibility, predictive analytics, and system resilience.




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