Electric Vehicles Charging and Discharging Optimization Based on Sand Cat Swarm Optimization (SCSO) Algorithm

Electric Vehicles Charging and Discharging Optimization Based on Sand Cat Swarm Optimization (SCSO) Algorithm | 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 Research Article Electric Vehicles Charging and Discharging Optimization Based on Sand Cat Swarm Optimization (SCSO) Algorithm Miaoheng Yang, Jialin Zhou, Wei Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6627232/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract This paper proposes a strategy for optimizing the charging and discharging of electric vehicles (EVs) using the Sand Cat Swarm Optimization (SCSO) algorithm, aiming to address the peak pressure on the grid caused by the increasing adoption of EVs. First, a Monte Carlo method is employed to construct a travel probability model for EVs, capturing key data such as charging duration, driving distance, and remaining battery power. Next, an optimization scheduling model for EV charging and discharging is established, incorporating a dynamic pricing mechanism. During the development stage of the SCSO algorithm, a roulette wheel strategy is introduced to update search angles, reducing the likelihood of local optima and enhancing optimization performance. Finally, the improved SCSO algorithm is applied to solve the multi-objective function, which aims to minimize grid load fluctuations, reduce user charging costs, and maximize user charging volume. The results demonstrate that the proposed strategy exhibits superior convergence speed and optimization capability, effectively mitigating peak-valley disparities in grid load and reducing residential charging costs, thereby significantly improving the grid's peak-shaving capacity. electric vehicles sand cat swarm optimization algorithm coordinated charging and discharging dynamic pricing strategy Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Jul, 2025 Reviews received at journal 02 Jul, 2025 Reviews received at journal 21 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 15 Jun, 2025 Reviewers agreed at journal 12 Jun, 2025 Reviewers agreed at journal 10 Jun, 2025 Reviewers invited by journal 13 May, 2025 Editor assigned by journal 12 May, 2025 Submission checks completed at journal 12 May, 2025 First submitted to journal 09 May, 2025 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-6627232","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":455707877,"identity":"f9cd6000-da61-4880-9cae-b0aeab6ef504","order_by":0,"name":"Miaoheng Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYLACxob/cozzHx848KGCeC3MxswNaYkHZ5whQUtie0OO8WHeFiJUGxw/e/jVzR1sjL0NZz4c4G1gkOcXO0BAy5m8NOvcMzzMko29Gw5I7mAwnDk7gYCWAzlmxrltEmyGzbwbDhieYUgwuE1Iy/k3IC0GPPbHeB4cSGwjRsuNHOPHuW0JEow9PAwHDhKjRfLGGzPm3LYDBowz2AwONpyRIOwXvvM5xp+BWuobZzA//vynwkaeX5qAFoUDDGwSSHwJnCrhQL6BgfkDYWWjYBSMglEwogEAqOpPDaozEJ0AAAAASUVORK5CYII=","orcid":"","institution":"School of Economics and Management, Shanghai University of Electric Power","correspondingAuthor":true,"prefix":"","firstName":"Miaoheng","middleName":"","lastName":"Yang","suffix":""},{"id":455707878,"identity":"a16ea868-e107-4f55-bb9a-ad650c5ff63e","order_by":1,"name":"Jialin Zhou","email":"","orcid":"","institution":"School of Economics and Management, Shanghai University of Electric Power","correspondingAuthor":false,"prefix":"","firstName":"Jialin","middleName":"","lastName":"Zhou","suffix":""},{"id":455707879,"identity":"be25aa5d-df82-4626-a998-ef457072c8fb","order_by":2,"name":"Wei Hu","email":"","orcid":"","institution":"School of Economics and Management, Shanghai University of Electric Power","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2025-05-09 09:23:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6627232/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6627232/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82700461,"identity":"62843c12-3c0f-4249-8b3d-7de652beebe0","added_by":"auto","created_at":"2025-05-14 09:28:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":428668,"visible":true,"origin":"","legend":"","description":"","filename":"ElectricVehiclesChargingandDischargingOptimizationBasedonSandCatSwarmOptimizationSCSOAlgorithm.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6627232/v1_covered_3c856094-822b-4117-b6f6-13053bb430ca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electric Vehicles Charging and Discharging Optimization Based on Sand Cat Swarm Optimization (SCSO) Algorithm","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"sustainable-energy-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Sustainable Energy Research","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"electric vehicles, sand cat swarm optimization algorithm, coordinated charging and discharging, dynamic pricing strategy","lastPublishedDoi":"10.21203/rs.3.rs-6627232/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6627232/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper proposes a strategy for optimizing the charging and discharging of electric vehicles (EVs) using the Sand Cat Swarm Optimization (SCSO) algorithm, aiming to address the peak pressure on the grid caused by the increasing adoption of EVs. 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