Recently updated on November 15th, 2024 at 11:54 am<\/p>","protected":false},"excerpt":{"rendered":"
The work proposes a probabilistic preventive control to ensure N-1 security in the presence of correlated uncertainties on renewables and loads. The control is decomposed into two successive linear programming problems, the first for active power and the second for voltage\/reactive power.<\/p>\n","protected":false},"author":93,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1324,1305,1307,1330],"targets":[1317],"pubblicazioni_tipologie":[773],"class_list":["post-188872","pubblicazioni","type-pubblicazioni","status-publish","hentry","tag-electricity-network-en","tag-energy-efficiency-en","tag-renewable-energy-en","tag-security-en","targets-research","pubblicazioni_tipologie-isi-article-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 continuous increase in renewable energy production, characterized by associated forecasting uncertainties, requires specific methodologies to support operators of power systems in managing security. This study proposes a probabilistic preventive control to ensure N-1 security in the presence of correlated uncertainties from renewable sources and loads.<\/p>\n
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By adopting a decoupled linear formulation of AC loadflow equations, the preventive control is decomposed into two successive linear programming problems. The first addresses active power issues, while the second focuses on voltage\/reactive power aspects. Specifically, in the active control problem, the algorithm combines third-order polynomial normal transformation, the Point Estimate Method (PEM), and the Cornish-Fisher expansion to model forecasting uncertainties and characterize chance constraint bounds in the problem.<\/p>\n
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The objective is to find the optimal setting for phase shifting transformer tap, conventional generation redispatch, and renewable curtailment at minimum cost to probabilistically satisfy N and N-1 security constraints on branch active power flows. The second phase resolves another linear programming problem aimed at minimizing adjustments to generator voltage setpoints to prevent violations of node voltages and branch limits due to reactive power flows, while respecting generator reactive power constraints.<\/p>\n
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Simulations conducted on an IEEE test network demonstrate the effectiveness of the proposed security control method in limiting the probability of security limit violations in N and N-1 states, including voltage\/reactive power constraints, under correlated uncertainties.<\/p>\n","scarica_file":false,"link_estreno":[{"link_text":"Download Publication","link":"https:\/\/www.mdpi.com\/1996-1073\/16\/4\/1812"}],"button":{"text":"","link":""},"referente_group":false,"data_emissione":"2023-02-11","autori":"E. Ciapessoni, D. Cirio, A. Pitto (RSE S.p.A.), F. Conte (Universit\u00e0 di Roma), S. Massucco, M. Saviozzi (Universit\u00e0 di Genova)","destinazione":"MDPI Energies Vol. 16 Issue 4, 11 February 2023","rif_rse":"22014173"},"satellite_post_url":""},"yoast_head":"\n