Information magazine of the Department of Industrial Engineering
Università di Trento
Information magazine of the Department of Industrial Engineering
Università di Trento
Global economic growth and the ongoing electrification of transport, data centers, and heating/cooling systems are driving a rapid rise in electricity consumption. According to the International Energy Agency (IEA), consumption is growing at annual rates between 3% and 4% (compared to around 2.5% a few years ago), with peaks between 5% and 7% in China.
Although renewable energy generation (mainly wind and solar) is expected to cover over 90% of the forecasted increase in electricity demand by 2025—surpassing coal-based generation by 2026—many uncertainties remain due to AI-based services, geopolitical instability, and climate change. Extreme weather events such as heatwaves or storms could cause unexpected consumption spikes or major infrastructure damage.
The only real certainty is that increasing fluctuations and imbalances between electricity supply and demand will occur. These will be exacerbated by the inherent volatility of renewables, potentially degrading power quality or even threatening grid stability.
The European Network of Transmission System Operators for Electricity (ENTSO-E) is working to define new criteria to identify when grid operating conditions become critical, so that timely and effective control actions can restore balance, enhance resilience, and minimize user disruption.
Such corrective actions depend on extensive and continuous monitoring. While traditionally focused on high- and medium-voltage networks, future systems will require dense monitoring capable of reconstructing and predicting grid states with high spatial and temporal resolution.
Key parameters include voltage frequency (around 50 Hz in Europe), which reflects the balance between generation and load and can be measured with millihertz precision in short times.
Other crucial data are the amplitude and phase of alternating voltages measured simultaneously across distant points in the grid. These synchronized measurements—enabled by GPS-equipped Phasor Measurement Units (PMUs)—provide a “snapshot” of grid conditions, ensuring full observability.
Another key parameter is the Rate of Change of Frequency (ROCOF), used to detect critical conditions. However, ROCOF measurements are highly sensitive to noise and abrupt phase or frequency variations, making their reliability difficult to guarantee.
Many techniques exist for measuring these quantities, but achieving both speed and accuracy remains challenging. Researchers at DII have long worked to meet—and anticipate—the demands of next-generation grid monitoring through numerous international collaborations. Key research areas include:
A recent collaboration with METAS has yielded major innovations in data fusion. Since frequency and ROCOF variations propagate across large areas, measurement uncertainty can be reduced by aggregating synchronized data from multiple locations.
A dedicated algorithm was developed to improve ROCOF reliability during critical events. The technique consists of three steps:
This approach reduces ROCOF measurement uncertainty by up to an order of magnitude, keeping it well below 0.1 Hz/s.
Further research aims to integrate frequency and ROCOF data to create a robust decision-support system. The collaboration with METAS has already earned best paper awards—first at the International Conference on Smart Grid Synchronized Measurements & Analytics (SGSMA) in Washington, D.C. (May 2024), and again at the IEEE International Workshop on Applied Measurements for Power Systems in Bucharest (September 2025).
Fig. 1 – IEEE 5-node test network used for preliminary algorithm simulations
Fig. 2 – Simplified 36-node model of the UK transmission grid for large-scale data fusion analysis
