The national target of the PNIEC for 2030 is to achieve a total photovoltaic (PV) capacity of 50 GW and a production of 72 TWh\/year. Therefore, in addition to carrying out new installations, it is necessary to develop solutions that help maintain high performance levels of the systems. To this end, RSE has initiated the development of diagnostic techniques for fault detection in PV systems and designed a Facility Guasti FV for the training and validation of diagnostic algorithms.<\/p>\n","protected":false},"author":464,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1328,1307],"targets":[1317],"rapporti_tipologie":[762],"class_list":["post-196756","rapporti","type-rapporti","status-publish","hentry","tag-photovoltaics","tag-renewable-energy-en","targets-research","rapporti_tipologie-report-en"],"acf":{"dont_show_hompage":true,"projects":{"ID":191040,"post_author":"464","post_date":"2024-07-10 15:54:17","post_date_gmt":"2024-07-10 13:54:17","post_content":"","post_title":"High-efficiency photovoltaics","post_excerpt":"This project è aims to foster the development of highly efficient and reduced-cost photovoltaic (PV) generation systems, both flat-plate and concentrating, that also help to optimize production of energy from plants installed in Italy.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"high-efficiency-photovoltaics","to_ping":"","pinged":"","post_modified":"2024-08-09 14:36:11","post_modified_gmt":"2024-08-09 12:36:11","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.rse-web.it\/progetti\/high-efficiency-photovoltaics\/","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":"
The national target set for 2030 in the National Integrated Energy and Climate Plan (PNIEC) is to achieve an installed photovoltaic capacity of 50 GW and a corresponding energy production of 72 TWh\/year. To meet this target, it is necessary not only to install new systems to ensure the specified power levels but also to maintain existing installations through solutions that enhance technology reliability and performance levels. There is significant interest in developing advanced monitoring methodologies that use diagnostic algorithms based on Machine Learning techniques. These methods can automatically recognize major fault conditions and accurately assess the performance of components and PV systems, thereby making the maintenance of PV system quality more efficient and cost-effective.<\/p>\n
To this end, this research by RSE has conducted a preliminary analysis of the main management costs and reviewed the current Operation and Maintenance (O&M) programs used by PV system operators. This analysis has led to hypotheses regarding economic losses related to faults in key components of a PV system lacking advanced maintenance services. Additionally, through Failure Mode and Effect Analysis (FMEA), the primary causes of faults in PV systems have been analyzed, and their impacts on energy and costs have been assessed. This activity, conducted by RSE in synergy with the EU GOPV project, has highlighted the components and sections of PV systems most prone to faults, leading to the development of solutions for the automatic identification of malfunctions.<\/p>\n
These activities have paved the way for the design of the experimental infrastructure named Facility Guasti FV, which will be physically established at RSE’s Milan laboratories. The Facility Guasti FV will simulate major system faults and identify electrical and thermal parameters used for fault condition recognition. The data acquired from simulation tests will enable the creation of a database for training and validating the automatic fault identification algorithms that RSE will develop in the upcoming phases of this Synthesis Report project.<\/p>\n","link_estreno":false,"scarica_file":[{"download_option":"download","file_name":"Download Report","download":{"ID":157430,"id":157430,"title":"20000436","filename":"20000436.pdf","filesize":2766701,"url":"https:\/\/www.rse-web.it\/wp-content\/uploads\/2019\/12\/20000436.pdf","link":"https:\/\/www.rse-web.it\/en\/rapporti\/20000436\/attachment\/20000436\/","alt":"","author":"93","description":"","caption":"","name":"20000436","status":"inherit","uploaded_to":132835,"date":"2021-05-28 14:29:10","modified":"2021-05-28 14:29:10","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":"D. Bombelli, G. Maugeri, V. Barone","rapporto":"","rif_rse":"20000436"},"satellite_post_url":""},"yoast_head":"\n