An energy management system for a virtual power plant that optimizes supply in the market and considers renewable sources is presented. The approach has been shown to increase profits by 23% compared to a non-optimized strategy and by 6% compared to deterministic optimization.<\/p>\n","protected":false},"author":93,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1540,1319,1307,1390],"targets":[1317],"pubblicazioni_tipologie":[773],"class_list":["post-197992","pubblicazioni","type-pubblicazioni","status-publish","hentry","tag-charging-stations","tag-energy-market","tag-renewable-energy-en","tag-transportation-electric-mobility","targets-research","pubblicazioni_tipologie-isi-article-en"],"acf":{"dont_show_hompage":true,"projects":{"ID":188407,"post_author":"93","post_date":"2024-06-13 15:10:16","post_date_gmt":"2024-06-13 13:10:16","post_content":"","post_title":"Regulatory support: market evolution; innovation in network design and management","post_excerpt":"The Project aims to study the regulation of the existing energy systems and the various proposals for its evolution, in order to assess its impact in terms of its effectiveness with respect to the objectives to be achieved, especially with a view to the decarbonization of the energy system itself.","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"regulatory-support-market-evolution-innovation-in-network-design-and-management","to_ping":"","pinged":"","post_modified":"2024-07-02 10:29:57","post_modified_gmt":"2024-07-02 08:29:57","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.rse-web.it\/progetti\/regulatory-support-market-evolution-innovation-in-network-design-and-management\/","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":"
In the present paper, an Energy Management System is proposed to optimally schedule and operate a Virtual Power Plant (VPP) composed of charging stations for e-vehicles, stationary batteries, and renewable energy sources. The model is capable to optimize the bidding process on the Day-Ahead Market (DAM) through a twostage stochastic formulation, which considers the uncertainties affecting the evaluation of the energy required for the next day.<\/p>\n
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The stochastic scenarios are generated through a Monte Carlo procedure and clustered by a reduced domain k-means algorithm. To manage in real-time the operation of the VPP, a new Rolling Horizon mixedinteger linear programming model is adopted. The effectiveness of the tools developed is proved by numerical simulations reproducing the different operating conditions of the VPP.<\/p>\n
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The benefits of the approach are confirmed by extensive analyses performed over a 4-month period. An increase of the profits of 23 % compared to a non-optimized strategy and of 6 % with respect to a deterministic optimization is observed.<\/p>\n","scarica_file":false,"link_estreno":[{"link_text":"Download Publication","link":"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0142061522006007"}],"button":{"text":"","link":""},"referente_group":false,"data_emissione":"2023-01-31","autori":"D. Falabretti, F. Gulotta (Politecnico di Milano), D. Siface (RSE S.p.A.)","destinazione":"International Journal of Electrical Power & Energy Systems, Vol. 144, N. 108604","rif_rse":"22014285"},"satellite_post_url":""},"yoast_head":"\n