{"id":22108,"date":"2022-06-06T15:44:59","date_gmt":"2022-06-06T14:44:59","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=22108"},"modified":"2022-07-31T17:55:22","modified_gmt":"2022-07-31T16:55:22","slug":"locating-ev-charging-facilities-model","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/locating-ev-charging-facilities-model\/22108\/","title":{"rendered":"Locating EV charging facilities assisted by a novel model"},"content":{"rendered":"<h2>A research team from <a href=\"https:\/\/www.ncsu.edu\/\" target=\"_blank\" rel=\"noopener\">North Carolina State University (NCSU)<\/a> has developed a model to assist drivers in locating EV charging facilities when required.<\/h2>\n<h3>A computational model capable of locating EV charging facilities<\/h3>\n<p>NCSU researchers have established a computational model that can be utilised to ascertain the optimal places for locating <a href=\"https:\/\/www.innovationnewsnetwork.com\/ev-charging-infrastructure-demand\/21772\/\">electric vehicle (EV) charging facilities<\/a>, as well as how powerful the charging stations can be without placing an unnecessary liability on the local power grid.<\/p>\n<p>\u201cUltimately, we feel the model can be used to inform the development of <a href=\"https:\/\/www.innovationnewsnetwork.com\/ev-charging-infrastructure\/\">EV charging infrastructure<\/a> at multiple levels, from projects aimed at supporting local commuters to charging facilities that serve interstate highway travel,\u201d explained Leila Hajibabai, corresponding author, and an Assistant Professor in NC State\u2019s Fitts Department of Industrial and Systems Engineering.<\/p>\n<p>EV drivers have noted that identifying the best sites for charging facilities is a complicated process. This is due to a series of variables, such as travel flow, user demand, and the requirements of the regional power infrastructure. In other words, where will people use it? And can it be supported by the power grid?<\/p>\n<p>This study was recently published in the journal <em>Computer-Aided Civil and Infrastructure Engineering. <\/em>The paper was co-authored by Asya Atik, a PhD student at NC State, and Amir Mirheli, a former PhD student at NC State.<\/p>\n<h3>A model that considers the power system and transportation<\/h3>\n<p>\u201cWe have developed a model that allows planners to optimise these decisions, serving the greatest number of people without taxing the power system,\u201d said Hajibabai.<\/p>\n<p>To date, a lot of work has been done to investigate how to efficiently deploy EV charging facilities. The research team discovered that many previous efforts focused on siting these facilities were based on what would work best for the power system, or what would work best from a transportation standpoint.<\/p>\n<p>\u201cVery little work has been done that addresses both,\u201d added Hajibabai. \u201cAnd those cases that looked at both power and transportation systems did not take into account the decisions that users make. Where do they want to charge their vehicles? What are their travel plans?<\/p>\n<p>\u201cThe best location for a charging facility from the power system\u2019s standpoint is often not the best location from a transportation systems standpoint. And the best location from a user\u2019s standpoint is often a third option. Our model looks at power systems, transportation systems, and user decision-making in order to find the best compromise.\u201d<\/p>\n<h3>The power system component of the model accounts for limitations<\/h3>\n<p>The power system element of the model accounts for the constraints of the power distribution network, such as its power flow, voltage, and current. The transportation factor of the central model accounts for the number of travellers, the routes that they take when travelling, and how far their EVs can move before recharging is required. To account for user decision-making, the model attempts to identify locations that will minimise travel time for users.<\/p>\n<p>\u201cPeople often do not want to go out of their way to charge their vehicles, so our model takes that into account,\u201d concluded Hajibabai.<\/p>\n<p>Scientists are currently in negotiations with state and local government officials, as well as power utilities, to utilise the model to improve the development of <a href=\"https:\/\/www.innovationnewsnetwork.com\/ev-charging-infrastructure\/\">EV charging infrastructure<\/a> in North Carolina.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A research team from North Carolina State University (NCSU) has developed a model to assist drivers in locating EV charging facilities when required. A computational model capable of locating EV charging facilities NCSU researchers have established a computational model that can be utilised to ascertain the optimal places for locating electric vehicle (EV) charging facilities, [&hellip;]<\/p>\n","protected":false},"author":21,"featured_media":22114,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[24425],"tags":[24128,3258,582,24404],"acf":[],"yoast_head":"\n<title>Locating EV charging facilities assisted by a novel model<\/title>\n<meta name=\"description\" content=\"A research team from North Carolina State University has developed a model to assist drivers in locating EV charging facilities when required.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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