The formation of snow sleeves on conductors is one of the most significant causes of faults on the grid. The collaboration between RSE and e-distribution led to the installation of three WILD 2.0 pilot stations to monitor them on MV lines. This monitoring enables the calibration of snow sleeve growth models for predictive and diagnostic purposes. The issue of freezing rain and the validation of the WOLF system during a major wet snowfall event were also addressed.<\/p>\n","protected":false},"author":464,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1324,1330],"targets":[1317],"rapporti_tipologie":[762],"class_list":["post-196895","rapporti","type-rapporti","status-publish","hentry","tag-electricity-network-en","tag-security-en","targets-research","rapporti_tipologie-report-en"],"acf":{"dont_show_hompage":true,"projects":{"ID":191053,"post_author":"464","post_date":"2024-07-10 16:51:45","post_date_gmt":"2024-07-10 14:51:45","post_content":"","post_title":"Models and tools for interventions, including preventive interventions, for defending and improving grid security and resilience","post_excerpt":"Models and tools for interventions, including preventive interventions, for defending and improving grid security and resilience","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"models-and-tools-for-interventions-including-preventive-interventions-for-defending-and-improving-grid-security-and-resilience","to_ping":"","pinged":"","post_modified":"2024-08-09 16:02:23","post_modified_gmt":"2024-08-09 14:02:23","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.rse-web.it\/progetti\/models-and-tools-for-interventions-including-preventive-interventions-for-defending-and-improving-grid-security-and-resilience\/","menu_order":0,"post_type":"progetti","post_mime_type":"","comment_count":"0","filter":"raw"},"order_posts":"","dont_show_search":false,"related_posts":false,"show_on_slider":false,"single_post_data":{"titolo_spot":"","post_content":"
To improve the resilience of the power system, it is necessary to understand the dynamics of meteorological phenomena that cause the most significant impacts. One event of particular interest to operators is wet snowfalls, as they form snow sleeves on the lines, leading to overloads, sometimes exceeding design limits.<\/p>\n
There are several models that simulate the snow sleeve load on conductors. RSE uses the Makkonen model, which simulates a cylindrical and conservative growth of the sleeve over time, using observed or forecasted weather variables during the snowfall as input data. The model was validated using measurements taken at the WILD station on a sample conductor of limited length.<\/p>\n
In Italy, the lack of snow sleeve load measurements on lines prevents direct verification of simulations, which can only be indirectly validated for significant cases by considering fault data.<\/p>\n
To overcome this limitation, within the collaboration between RSE and e-distribution, the NEWMAN project was launched with the installation of three WILD 2.0 pilot stations. The project aims to study the formation of snow sleeves on medium-voltage (MV) lines in areas of the country with a high risk of faults. The stations are equipped with ice-free weather sensors, load cells on conductors and aerial cables to measure sleeve loads, cameras on towers, and IoT sensors. This is the first time this type of experimentation has been conducted in Italy.<\/p>\n
The stations provide snow sleeve loads on conductors and the weather conditions that cause them. The measurements feed into a database for quick extraction and analysis, which will allow for the calibration of the sleeve model used in WOLF and MERIDA with real data. It also supports CT 11\/7 of CEI, which aims to “Verify and update the expected load maps in CEI EN 50341-2-13”. The issue of freezing rain was also addressed, focusing on its characterization and prediction, as this phenomenon is particularly problematic for MV networks and railways. The first freezing rain forecasts are available on the WOLF webGIS site.<\/p>\n
Finally, the good forecasting capability of WOLF was confirmed during the wet snowfall event on February 5-6, 2015, in Emilia Romagna and Lombardy, using fault data. This event caused up to 330,000 outages, lasting more than 8 hours.<\/p>\n","link_estreno":false,"scarica_file":[{"download_option":"download","file_name":"Download Report","download":{"ID":105790,"id":105790,"title":"19012835-319198.pdf","filename":"19012835-319198.pdf","filesize":23303867,"url":"https:\/\/www.rse-web.it\/wp-content\/uploads\/2021\/03\/19012835-319198.pdf","link":"https:\/\/www.rse-web.it\/en\/rapporti\/19012835\/19012835-319198\/","alt":"","author":"464","description":"19012835-319198.pdf","caption":"","name":"19012835-319198","status":"inherit","uploaded_to":132812,"date":"2021-12-31 00:00:00","modified":"2021-03-17 12:49:26","menu_order":0,"mime_type":"application\/pdf","type":"application","subtype":"pdf","icon":"https:\/\/www.rse-web.it\/wp-includes\/images\/media\/document.png"}}],"button":{"text":"","link":""},"referente_group":false,"data_emissione":"2019-12-31","autori":"M. Lacavalla, P. Marcacci, R. Bonanno","rapporto":"","rif_rse":"19012835"},"satellite_post_url":""},"yoast_head":"\n