As renewable energy penetration increases, grid stability and forecasting accuracy are becoming critical concerns for TSOs, DSOs, and energy market participants. One challenge is the intermittency of solar and wind generation, which makes accurate forecasting essential for balancing supply and demand while maintaining grid reliability.
The RESPONDENT project is tackling this challenge by integrating AI-driven power generation and demand forecasting with Galileo-enabled Phasor Measurement Units (PMUs) for nanosecond-level time synchronization—a key enabler for real-time grid monitoring and control.
An upcoming pilot demonstration in Barcelona and online will test and demonstrate these technologies in a real-world setting, integrating:
✔ Advanced AI/ML forecasting models using Copernicus Earth Observation data
✔ Galileo-enabled PMUs for ultra-precise grid monitoring
✔ Real-time data integration to support demand-side response and congestion management
The results will highlight how improved forecasting accuracy and synchronized grid monitoring can help utilities:
🔹 Optimize electricity planning and reduce reliance on backup generation
🔹 Enhance voltage control and congestion management in renewable-dominated grids
🔹 Strengthen Europe’s energy security with a non-EU-dependent time synchronization solution
We’d love to hear from grid operators, energy traders, and utility professionals - how is your organization leveraging AI and space-based data for smarter grid operations?
For more details on RESPONDENT, visitÂ
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