Enhancing Wind Energy Systems With Bi-directional Dc-dc Voltage Converters and Dynamic Wind Pattern Prediction Algorithm

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Abstract This research discussed the bi-directional DC-DC voltage converter design and analysis for the wind energy system. This system is made up of batteries, an Axial Flux Permanent Magnet Wind Generator (AFPMWG), and a bi-directional DC to DC voltage converter. Dynamic Wind Pattern Prediction ( DWPP) incorporates a sophisticated algorithm used for mitigating voltage fluctuation and also ensures continuous and smooth power supply for all operating conditions. DWPP algorithm utilizes historical wind data and real-time environmental factors to predict wind patterns in the near future. By forecasting wind speeds and directions, the DWPP algorithm enables the MPPT method enhanced with PSO controller to proactively adjust the turbine's operating parameters, optimizing energy extraction even before the wind conditions change. The bi-directional DC to DC voltage converter has buck and boost converters which are connected to cascade and results in bidirectional power flow. These innovations focused on enhancing the efficiency and reliability of wind energy systems. By integrating advanced control algorithms and real-time monitoring capabilities, these converters dynamically adjust the operating conditions of wind turbines to maximize power extraction from the wind. This predictive capability allows the energy management system to preemptively adjust operational parameters, thus optimizing energy capture and distribution. MATLAB simulation result was analyzed with comparison to real-life data for better understanding.
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Enhancing Wind Energy Systems With Bi-directional Dc-dc Voltage Converters and Dynamic Wind Pattern Prediction 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 Enhancing Wind Energy Systems With Bi-directional Dc-dc Voltage Converters and Dynamic Wind Pattern Prediction Algorithm Keerthana K, Jaya N This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7747422/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 This research discussed the bi-directional DC-DC voltage converter design and analysis for the wind energy system. This system is made up of batteries, an Axial Flux Permanent Magnet Wind Generator (AFPMWG), and a bi-directional DC to DC voltage converter. Dynamic Wind Pattern Prediction ( DWPP) incorporates a sophisticated algorithm used for mitigating voltage fluctuation and also ensures continuous and smooth power supply for all operating conditions. DWPP algorithm utilizes historical wind data and real-time environmental factors to predict wind patterns in the near future. By forecasting wind speeds and directions, the DWPP algorithm enables the MPPT method enhanced with PSO controller to proactively adjust the turbine's operating parameters, optimizing energy extraction even before the wind conditions change. The bi-directional DC to DC voltage converter has buck and boost converters which are connected to cascade and results in bidirectional power flow. These innovations focused on enhancing the efficiency and reliability of wind energy systems. By integrating advanced control algorithms and real-time monitoring capabilities, these converters dynamically adjust the operating conditions of wind turbines to maximize power extraction from the wind. This predictive capability allows the energy management system to preemptively adjust operational parameters, thus optimizing energy capture and distribution. MATLAB simulation result was analyzed with comparison to real-life data for better understanding. Wind Energy Systems Bi-Directional DC-DC Converter Dynamic Wind Pattern Prediction MPPT with PSO Controller Efficiency Optimization 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. 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This system is made up of batteries, an Axial Flux Permanent Magnet Wind Generator (AFPMWG), and a bi-directional DC to DC voltage converter. Dynamic Wind Pattern Prediction\u003cstrong\u003e (\u003c/strong\u003eDWPP)\u003cstrong\u003e \u003c/strong\u003eincorporates a sophisticated algorithm used for mitigating voltage fluctuation and also ensures continuous and smooth power supply for all operating conditions. DWPP algorithm utilizes historical wind data and real-time environmental factors to predict wind patterns in the near future. By forecasting wind speeds and directions, the DWPP algorithm enables the MPPT method enhanced with PSO controller to proactively adjust the turbine's operating parameters, optimizing energy extraction even before the wind conditions change. The bi-directional DC to DC voltage converter has buck and boost converters which are connected to cascade and results in bidirectional power flow. These innovations focused on enhancing the efficiency and reliability of wind energy systems. By integrating advanced control algorithms and real-time monitoring capabilities, these converters dynamically adjust the operating conditions of wind turbines to maximize power extraction from the wind. This predictive capability allows the energy management system to preemptively adjust operational parameters, thus optimizing energy capture and distribution. \u0026nbsp;MATLAB simulation result was analyzed with comparison to real-life data for better understanding.\u003c/p\u003e","manuscriptTitle":"Enhancing Wind Energy Systems With Bi-directional Dc-dc Voltage Converters and Dynamic Wind Pattern Prediction Algorithm","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-27 10:58:42","doi":"10.21203/rs.3.rs-7747422/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"50abaa7a-b9d0-4181-8b1f-53374d456394","owner":[],"postedDate":"November 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-28T13:08:49+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-27 10:58:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7747422","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7747422","identity":"rs-7747422","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

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