Recently updated on July 2nd, 2024 at 02:36 pm<\/p>","protected":false},"excerpt":{"rendered":"
The report presents evolutions of the SPOPSI procedure, which, from historical wind, photovoltaic and load power series, creates new series with the same statistical properties but with significant variability. These series can be used as inputs to procedures based on the Monte Carlo method for probabilistic simulation of the electrical system. Dependence on weather variables is modeled; climate projections are exploited in the generation of future power and load series.<\/p>\n","protected":false},"author":93,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1325,1328,1359],"targets":[1317],"rapporti_tipologie":[762],"class_list":["post-190255","rapporti","type-rapporti","status-publish","hentry","tag-electrical-system","tag-photovoltaics","tag-wind","targets-research","rapporti_tipologie-report-en"],"acf":{"dont_show_hompage":true,"projects":{"ID":188403,"post_author":"464","post_date":"2024-06-13 15:10:08","post_date_gmt":"2024-06-13 13:10:08","post_content":"","post_title":"Evolution, planning, scheduling and operation of power grids","post_excerpt":"The goal of the project is the pursuit of efficient management of the Italian electricity system that meets, in evolving scenarios, criteria of security and quality of operation, adequacy and resilience, ensuring a system-based approach. ","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"evolution-planning-scheduling-and-operation-of-power-grids","to_ping":"","pinged":"","post_modified":"2024-07-02 10:31:45","post_modified_gmt":"2024-07-02 08:31:45","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.rse-web.it\/progetti\/evolution-planning-scheduling-and-operation-of-power-grids\/","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 Stochastic Power Profile Simulation (SPOPSI) procedure analyzes historical time series of wind power, photovoltaic power and electric load and generates new synthetic series stochastically, maintaining the statistical properties of the original series. The synthetic series can be used as inputs to procedures based on the Monte Carlo method for probabilistic power system simulation, particularly for adequacy assessments.<\/p>\n
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SPOPSI_load is the section of SPOPSI devoted to load, modeled through temperature dependence; this report proposes a comparison of load series generated with the variations in temperature provided by different climate scenarios. SPOPSI_load captures the fact that an increase in summer temperature causes an increase in consumption, while in winter, consumption decreases due to the change in the use of cooling\/heating systems.<\/p>\n
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Regarding the section of SPOPSI devoted to wind power, we show the model assumed for the dependence of the series on temperature and wind speed: the annual trend in power is a function of the annual trends in meteorological variables. Historical meteorological data come from the MERIDA HRES reanalysis dataset; climate forecasts for model construction are generated from Euro-CORDEX models for the most pessimistic scenario in terms of greenhouse gas emissions and global warming (Representative Concentration Pathway RCP8.5), bias-corrected against MERIDA HRES data; point series are then aggregated regionally to be homogeneous with power series. The stochastic components of the series are clustered according to their correlation, and each cluster identifies a stochastic process.<\/p>\n
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To account for future evolutions in wind turbine technology, an additional function allows the equivalent hours of the power series to be modified by distributing the increase in power output according to a hypothetical wind-power characteristic that, with the same wind, generates more power.
\nComparison between the synthetic series generated by SPOPSI_wind and the historical test series shows that the statistical properties are preserved, but variability is present that makes the individual generated series significantly different from each other, as required by probabilistic analyses of the electricity system based on the Monte Carlo method. Finally, the report presents an application in a 2050 scenario.<\/p>\n","link_estreno":false,"scarica_file":[{"download_option":"download","file_name":"Download Report","download":{"ID":186003,"id":186003,"title":"22013919","filename":"22013919.pdf","filesize":10159709,"url":"https:\/\/www.rse-web.it\/wp-content\/uploads\/2024\/02\/22013919.pdf","link":"https:\/\/www.rse-web.it\/en\/rapporti\/procedura-spopsi-per-generare-serie-temporali-di-grandezze-stocastiche-sviluppo-della-dipendenza-della-potenza-eolica-da-variabili-metereologiche-e-dalla-tecnologia-indagine-della-dipendenza-della-p\/attachment\/22013919\/","alt":"","author":"93","description":"","caption":"","name":"22013919","status":"inherit","uploaded_to":186002,"date":"2024-02-12 15:02:52","modified":"2024-02-12 15:02:52","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":"2022-12-31","autori":"G. Ceresa, A. Trevisiol, M. R. Rapizza, R. Bonanno, M. Riva (RSE S.p.A.)","rapporto":"","rif_rse":"22013919"},"satellite_post_url":""},"yoast_head":"\n