Unlocking electric vehicle flexibility in microgrids via lightweight on-charger coordination

Unlocking electric vehicle flexibility in microgrids via lightweight on-charger coordination | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unlocking electric vehicle flexibility in microgrids via lightweight on-charger coordination Yi Wang, Yehui Li, Xueyuan Cui, Chongqing Kang, Thomas Morstyn This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9115262/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Uncoordinated electric vehicle charging drives extreme peak demand and grid congestion, severely compromising microgrid stability and economics. To address this challenge, as the interface between vehicles and grids, on-board chargers hold the potential to be transformed into intelligent agents that actively balance microgrid constraints with mobility requirements. However, existing distributed schemes impose prohibitive computational and communication burdens on these resource-constrained edge chargers. Here, we propose a lightweight distributed coordination framework that embeds edge intelligence directly into on-board chargers for autonomous schedule optimization. Validated on a high-fidelity hardware-in-the-loop platform simulating complex microgrid cyber-physical dynamics, our framework reduces memory consumption by 96.1% and communication overhead by 74.3% compared to traditional schemes. Moreover, unlocking this hardware-level flexibility achieves a 10.8% profit increase over the status quo. Importantly, the proposed framework promises profound economic, environmental, and social benefits for the future energy landscape. Physical sciences/Engineering/Electrical and electronic engineering Physical sciences/Energy science and technology/Energy modelling Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Supplementaryinformation.pdf Supplementary information for the manuscript Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9115262","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":605782944,"identity":"7a6a25e0-0c8d-4935-8559-1b7898ed9869","order_by":0,"name":"Yi 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