In this report, several issues related to forecasting and monitoring systems for the main weather threats that interfere with the power system, from wet snowfall to heat waves and extreme wind episodes, were addressed. For each threat, in-depth work has been carried out with respect to previous years of research, in order to be able to improve the quality of forecasting of the above-mentioned phenomena.

With regard to wet snowfall, a new methodology for its identification has been investigated, starting from modeling variables related to the mixing ratio of the solid and liquid component of precipitation. This new methodology, which is still in the preliminary study phase, makes it possible to justify, on a physical level, snowfall episodes with sleeve formation even with significant masses, but which, according to the currently used thermal window methodology, would not have been classifiable as wet snowfall. Through the WILD and WILD 2.0 monitoring stations, a number of significant wet snowfall events affecting northern Italy in December 2022 were analyzed and the performance of the WOLF forecasting system in conjunction with these events was evaluated.

ELISAm, a new monitoring system entirely implemented by RSE and allowing the measurement of the variation of the deflection, the rotation of High Voltage (HV) conductors and, if present, the diameter of the snow sleeve, is also presented. During the year, interest emerged from Terna to install 2 ELISAm prototypes at the Cencenighe-Moena line.

The system was put into operation in early winter providing the first images and processing. Relative to the forecasting of the high wind threat, the feasibility in adopting the Analog Ensemble statistical downscaling technique was investigated to derive a more accurate estimate of wind intensity, starting from the wind forecasting system currently in use, especially in territories with complex orography by exploiting wind data from the new Italian Wind Atlas (AEOLIAN).

Finally, in relation to the issue of faults on underground cables of the Medium Voltage (MV) distribution network, in conjunction with heat waves, the previously developed fault prediction system was refined. Specifically, a coupling was made with the Land Surface Model Noah-Multiparameterization (Noah-MP), driven by weather forcings from ECMWF’s Integrated Forecast System (IFS) weather model. This coupling allows the use of an urban-type land use, which is more realistic for the city of Milan, and also allows the selection of the best performing soil type in terms of describing soil temperature and moisture profiles.