Optimal Control Strategies for Sustainable Energy Management in Electric Power Grids: A Hybrid Model Predictive Approach

Optimal Control Strategies for Sustainable Energy Management in Electric Power Grids: A Hybrid Model Predictive Approach | 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 Optimal Control Strategies for Sustainable Energy Management in Electric Power Grids: A Hybrid Model Predictive Approach SeyedHamed MirMohammadAli Roudaki, Kaveh Yazdani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4204516/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Energy infrastructure development in rural and remote areas of the planet is key to sustaining human development. This study establishes an optimal control strategy that can efficiently manage an electric grid comprised of various renewable and non-renewable energy sources for a medium sized community. Simple power dynamics are modeled and used for representing the components present on the grid. A hybrid model predictive control scheme is implemented for choosing an optimal mode and set of inputs for the system for tracking both a constant and load-varying power demand profile. hybrid power supervisory model predictive control smart grids Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4204516","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286544037,"identity":"7bfe6aa5-d5dd-4925-a0d4-d9c1a4c64d88","order_by":0,"name":"SeyedHamed MirMohammadAli Roudaki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYBACAxDBAyIOsDEc+AATTiBWy8EZDAwSpGlh5oFpwQfM2U8nPni7xyax7/ixxMM2NYfrGNgPP2B4uAe3Fsue3M2Gc56lJc48k3bgcM6xwxIMPGkGDAnP8DjsQO42aZ4DhxM3HEhvOJzDBtTCkAP0ywE8Ws6/3f4brOX884bDFv+AWvjfENByI3cbM1jLDaDDGNuAWiQI2XLj7WbJOQfSjGfeeJZwsLcvXbJN4pnBAfwOy9344c0BG9m+82nGH358s+bn509++PAHHi2YgA2ISdIwCkbBKBgFowATAACdh14X+pgpKQAAAABJRU5ErkJggg==","orcid":"","institution":"Amirkabir University of Technology","correspondingAuthor":true,"prefix":"","firstName":"SeyedHamed","middleName":"MirMohammadAli","lastName":"Roudaki","suffix":""},{"id":286544041,"identity":"829c4501-981a-497b-9017-0e511c4ef84b","order_by":1,"name":"Kaveh Yazdani","email":"","orcid":"","institution":"Hamedan University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Kaveh","middleName":"","lastName":"Yazdani","suffix":""}],"badges":[],"createdAt":"2024-04-02 07:05:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4204516/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4204516/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57867260,"identity":"01f246d1-1abf-40c7-a24a-9172404a2144","added_by":"auto","created_at":"2024-06-06 16:01:01","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":769095,"visible":true,"origin":"","legend":"","description":"","filename":"OptimalControlStrategiesforSustainableEnergyManagementinElectricPowerGridsAHybridModelPredictiveApproach.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4204516/v1_covered_bd8b8feb-7fed-477e-a56e-edcd8e0e8e23.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimal Control Strategies for Sustainable Energy Management in Electric Power Grids: A Hybrid Model Predictive Approach","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"hybrid, power, supervisory, model predictive control, smart grids","lastPublishedDoi":"10.21203/rs.3.rs-4204516/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4204516/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEnergy infrastructure development in rural and remote areas of the planet is key to sustaining human development. 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