{"id":188840,"date":"2024-06-21T14:15:53","date_gmt":"2024-06-21T12:15:53","guid":{"rendered":"https:\/\/www.rse-web.it\/pubblicazioni\/characterization-of-electric-consumers-through-an-automated-clustering-pipeline\/"},"modified":"2024-07-02T14:24:52","modified_gmt":"2024-07-02T12:24:52","slug":"characterization-of-electric-consumers-through-an-automated-clustering-pipeline","status":"publish","type":"pubblicazioni","link":"https:\/\/www.rse-web.it\/en\/publications\/characterization-of-electric-consumers-through-an-automated-clustering-pipeline\/","title":{"rendered":"Characterization of electric consumers through an automated clustering pipeline"},"content":{"rendered":"<p class=\"last-updated-date\">Recently updated on July 2nd, 2024 at 02:24 pm<\/p>","protected":false},"excerpt":{"rendered":"<p>Cluster analysis of daily load profiles represents an effective technique for classifying and aggregating electrical users based on their actual consumption patterns.<\/p>\n","protected":false},"author":93,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"tags":[1419,1315],"targets":[1317],"pubblicazioni_tipologie":[778],"class_list":["post-188840","pubblicazioni","type-pubblicazioni","status-publish","hentry","tag-energy-consumption","tag-smart-grids-en","targets-research","pubblicazioni_tipologie-paper-en"],"acf":{"dont_show_hompage":true,"order_posts":"","dont_show_search":false,"projects":false,"related_posts":false,"show_on_slider":false,"single_post_data":{"titolo_spot":"","post_content":"<p>Among other purposes, it can be leveraged as a preliminary phase for load forecasting, which is similarly applied to consumers within the same cluster. Numerous clustering algorithms have been proposed and developed in the literature, and selecting the most appropriate set of clustering parameters is crucial to ensure reliable results. This paper introduces an automated service suitable for repeated clustering analysis.<\/p>\n<p>&nbsp;<\/p>\n<p>The pipeline can process a set of generic time series data and is easily adjustable to test other input clustering parameters; hence, it can be used to find the best parameter set for specific datasets. Furthermore, it facilitates repeated characterization of real-time load profiles aimed at detecting sudden changes in consumer behaviors and variable external conditions, which impact real power forecasting activity on a short time scale.<\/p>\n","scarica_file":false,"link_estreno":[{"link_text":"Download Publication","link":"https:\/\/arxiv.org\/abs\/2205.04737"}],"button":{"text":"","link":""},"referente_group":false,"data_emissione":"2022-07-01","autori":"F. Soldan, A. Maldarella, G. Paludetto, E. Bionda (RSE S.p.A.), F. Belloni (Unareti S.p.A.), S. Grillo (Politecnico di Milano)","destinazione":"EEEIC2022  22nd annual conference of the International Conference on Environmental and Electrical Engineering, Prague June 28 - July 1, 2022 ","rif_rse":"22004657"},"satellite_post_url":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Characterization of electric consumers through an automated clustering pipeline - RSE<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.rse-web.it\/publications\/characterization-of-electric-consumers-through-an-automated-clustering-pipeline\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Characterization of electric consumers through an automated clustering pipeline - RSE\" \/>\n<meta property=\"og:description\" content=\"Cluster analysis of daily load profiles represents an effective technique for classifying and aggregating electrical users based on their actual consumption patterns.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.rse-web.it\/publications\/characterization-of-electric-consumers-through-an-automated-clustering-pipeline\/\" \/>\n<meta property=\"og:site_name\" content=\"RSE\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-02T12:24:52+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.rse-web.it\/publications\/characterization-of-electric-consumers-through-an-automated-clustering-pipeline\/\",\"url\":\"https:\/\/www.rse-web.it\/publications\/characterization-of-electric-consumers-through-an-automated-clustering-pipeline\/\",\"name\":\"Characterization of electric consumers through an automated clustering pipeline - 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