NPC type three-level PV grid-connected inverter S-FCS-MPC control strategy

NPC type three-level PV grid-connected inverter S-FCS-MPC control strategy | 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 NPC type three-level PV grid-connected inverter S-FCS-MPC control strategy Aimin An, Yan Wu, Xiangui Li, Yuwei Qin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5371623/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 Due to constraints from external environmental factors and grid faults, traditional maximum power point tracking (MPPT) and inverter control methods often fail to achieve optimal power output in photovoltaic systems.This can result in misclassification and suboptimal dynamic performance. To address these challenges, we propose a simplified finite set model predictive control (S-FCS-MPC) for grid-connected PV systems. Our system employs a neutral point-clamped (NPC) topology, integrating MPPT and space vector modulation (SVPWM) techniques.Initially, high efficiency is attained by controlling the front stage with an adaptive particle swarm optimization-conductance increment (APSO-INC) approach to accurately identify the maximum power point, while model predictive control (MPC) is used to track the MPP and regulate the boost converter. Subsequently, we simplify the voltage vector for the NPC-type 3-level PV grid-connected inverter, selecting the optimal voltage vector based on the optimal value function, and applying the corresponding switching states to the inverter’s power semiconductors to facilitate grid connection.The proposed system is simulated and evaluated under various dynamic conditions using Matlab/Simulink. The results demonstrate that our algorithm effectively maintains DC-side voltage balance and significantly reduces computational effort compared to traditional methods, confirming its feasibility. PV grid-connected power system Fast vector selection model predictive control Maximum power tracking technique NPC type inverter 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. 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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-5371623","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":373719518,"identity":"10935034-546c-456f-a2c7-b8cd7025923a","order_by":0,"name":"Aimin An","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYJCCAwwGDDJ87I2NDz+QooWHjedws7EEKTbxsEmktwnwEKOUf3bzw0M3Cu7wsEk+bGOQYLCT020goEXizjGDwzkGz3jYpBPbHhQwJBubHSBkzY0EkJbDIC3tBhIMBxK3EdIifyP9A0SL5ME2CR5itBjcyIHaIsFIpBbDGzkFEC08icBANiDCL3I30jd/zvlzWI6f/fjDhx8q7OQIex/NnaQpHwWjYBSMglGAAwAA+Z5Av2z0PD8AAAAASUVORK5CYII=","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Aimin","middleName":"","lastName":"An","suffix":""},{"id":373719522,"identity":"34966778-ae00-4ee9-85a5-fda47e2c3ae7","order_by":1,"name":"Yan Wu","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wu","suffix":""},{"id":373719524,"identity":"406dd156-0607-4463-9cfe-e5141ee46471","order_by":2,"name":"Xiangui Li","email":"","orcid":"","institution":"Lanzhou University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Xiangui","middleName":"","lastName":"Li","suffix":""},{"id":373719525,"identity":"d30605f0-7f1c-45ed-a341-79ab355bd237","order_by":3,"name":"Yuwei Qin","email":"","orcid":"","institution":"Weinan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yuwei","middleName":"","lastName":"Qin","suffix":""}],"badges":[],"createdAt":"2024-11-01 08:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5371623/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5371623/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69725615,"identity":"97035b64-fc9e-4de4-a8c4-c57bc8f7ff7a","added_by":"auto","created_at":"2024-11-24 10:16:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1926212,"visible":true,"origin":"","legend":"","description":"","filename":"NPCtypethreelevelPVgridconnectedinverterSFCSMPCcontrolstrategy.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5371623/v1_covered_ff472fef-ab62-4aad-ac44-e39236d8ed1a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"NPC type three-level PV grid-connected inverter S-FCS-MPC control strategy","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":"PV grid-connected power system, Fast vector selection model predictive control, Maximum power tracking technique, NPC type inverter","lastPublishedDoi":"10.21203/rs.3.rs-5371623/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5371623/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDue to constraints from external environmental factors and grid faults, traditional maximum power point tracking (MPPT) and inverter control methods often fail to achieve optimal power output in photovoltaic systems.This can result in misclassification and suboptimal dynamic performance. To address these challenges, we propose a simplified finite set model predictive control (S-FCS-MPC) for grid-connected PV systems. Our system employs a neutral point-clamped (NPC) topology, integrating MPPT and space vector modulation (SVPWM) techniques.Initially, high efficiency is attained by controlling the front stage with an adaptive particle swarm optimization-conductance increment (APSO-INC) approach to accurately identify the maximum power point, while model predictive control (MPC) is used to track the MPP and regulate the boost converter. Subsequently, we simplify the voltage vector for the NPC-type 3-level PV grid-connected inverter, selecting the optimal voltage vector based on the optimal value function, and applying the corresponding switching states to the inverter\u0026rsquo;s power semiconductors to facilitate grid connection.The proposed system is simulated and evaluated under various dynamic conditions using Matlab/Simulink. 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