Identification of Representative Wind Power Fluctuation Patterns for Water Electrolysis Device Stress Testing - A Data Mining Approach

Identification of Representative Wind Power Fluctuation Patterns for Water Electrolysis Device Stress Testing - A Data Mining 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 Identification of Representative Wind Power Fluctuation Patterns for Water Electrolysis Device Stress Testing - A Data Mining Approach Kyong Jin Choi, Sanghoon Kim, Yongchai Kwon, Min Kyu Sim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4520985/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Sep, 2024 Read the published version in Korean Journal of Chemical Engineering → Version 1 posted 5 You are reading this latest preprint version Abstract Wind power generation is expected to greatly contribute to the future of humanity as a promising source of renewable energy. However, the high variability inherent in wind is a challenge that hinders stable power generation. To utilize wind power as a primary energy source, integration with a polymer electrolyte membrane water electrolysis (PEMWE) system is proposed. Yet, PEMWE is known to suffer from degradation when exposed to input power patterns with high variability. This poses challenges to its commercialization. This necessitates stress testing with various wind power fluctuations during the production process of the devices. This study investigates representative patterns of wind power fluctuation so that these patterns can be used for the stress testing process. We employ data-mining techniques, including the Swing Door Algorithm and k-means clustering, to identify these patterns by analyzing wind power generation data at a 10-second interval. As a result, the five most representative wind power ramps are presented. This study provides practical guidelines for the development process of expensive devices for wind power generation, thereby promoting the active utilization of wind power generation. Wind power generation Wind power fluctuation k-means clustering Swing Door Algorithm Stress testing Full Text Cite Share Download PDF Status: Published Journal Publication published 23 Sep, 2024 Read the published version in Korean Journal of Chemical Engineering → Version 1 posted Editorial decision: Minor Revisions Needed 15 Jul, 2024 Reviewers agreed at journal 17 Jun, 2024 Reviewers invited by journal 17 Jun, 2024 Editor assigned by journal 06 Jun, 2024 First submitted to journal 03 Jun, 2024 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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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-4520985","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":315423527,"identity":"8627da21-f155-4327-9345-9ce4bedd0832","order_by":0,"name":"Kyong Jin Choi","email":"","orcid":"","institution":"Seoul National University of Science \u0026 Technology","correspondingAuthor":false,"prefix":"","firstName":"Kyong","middleName":"Jin","lastName":"Choi","suffix":""},{"id":315423528,"identity":"b1eaece5-c9b1-45d2-8498-b42b95c02dec","order_by":1,"name":"Sanghoon Kim","email":"","orcid":"","institution":"Seoul National University of Science \u0026 Technology","correspondingAuthor":false,"prefix":"","firstName":"Sanghoon","middleName":"","lastName":"Kim","suffix":""},{"id":315423529,"identity":"bc5dbf58-5923-48bc-be9c-f64d62cce752","order_by":2,"name":"Yongchai Kwon","email":"","orcid":"","institution":"Seoul National University of Science \u0026 Technology","correspondingAuthor":false,"prefix":"","firstName":"Yongchai","middleName":"","lastName":"Kwon","suffix":""},{"id":315423530,"identity":"e2f02b22-e770-490d-8052-ef6e1c1ba678","order_by":3,"name":"Min Kyu Sim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIie3RoQrCQBzH8f+4YJmsaplPIGwIPo+HweK6Ycw7BC17AAXxGUzm6R9muWGdYJgI5oHFInhnVc7ZDPdNv/KBP/wBTKZ/zAZIYKQWYaC2WhWIUMvirDIBa/oLacf78+64ilynQWdFGZ7AmSWkM9KQbhZ7GGyw05xTzufpFRqiR6jQkYMNkiR0nVM+qTMEyIFsmZbUCgyW0fhFHpK0vpKMycMY6XmKWJJ4klAtEcLDYYr+Ij7zRZyi7Qs68fVkcLkNw6jl1PpJeQ/RdfeITR15S/7J+gmYTCaT6UNPwE5YlgA1HEkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0616-1449","institution":"Seoul National University of Science \u0026 Technology","correspondingAuthor":true,"prefix":"","firstName":"Min","middleName":"Kyu","lastName":"Sim","suffix":""}],"badges":[],"createdAt":"2024-06-03 09:59:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4520985/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4520985/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11814-024-00286-z","type":"published","date":"2024-09-23T15:57:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":65627302,"identity":"eed27393-899c-4f98-9cf5-cdc0fe14b7c5","added_by":"auto","created_at":"2024-09-30 16:14:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1057275,"visible":true,"origin":"","legend":"","description":"","filename":"IdentificationofRepresentativeWindPowerFluctuation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4520985/v1_covered_02541e91-80ad-4076-86c7-108a78c42fd4.pdf"}],"financialInterests":"","formattedTitle":"Identification of Representative Wind Power Fluctuation Patterns for Water Electrolysis Device Stress Testing - A Data Mining Approach","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":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"korean-journal-of-chemical-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"kjce","sideBox":"Learn more about [Korean Journal of Chemical Engineering](http://link.springer.com/journal/11814)","snPcode":"11814","submissionUrl":"https://www.editorialmanager.com/kjce/default2.aspx","title":"Korean Journal of Chemical Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Subscription","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Wind power generation, Wind power fluctuation, k-means clustering, Swing Door Algorithm, Stress testing","lastPublishedDoi":"10.21203/rs.3.rs-4520985/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4520985/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWind power generation is expected to greatly contribute to the future of humanity as a promising source of renewable energy. 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