A Hybrid Active Frequency Drift and Pearson Correlation Method for Islanding Detection in Grid-Connected Photovoltaic Systems

A Hybrid Active Frequency Drift and Pearson Correlation Method for Islanding Detection in Grid-Connected Photovoltaic Systems | 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 A Hybrid Active Frequency Drift and Pearson Correlation Method for Islanding Detection in Grid-Connected Photovoltaic Systems Ahmed G. Abo-Khalil, Ahmed Sobhy, Khairy Sayed, A. Elnady, Mohamed A. Mosbah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8777575/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Islanding detection remains a critical technical challenge in grid-connected photovoltaic (PV) systems, as delayed or missed detection can compromise both system safety and grid reliability. Conventional Active Frequency Drift (AFD)–based techniques, although effective, suffer from relatively large non-detection zones (NDZs) and prolonged detection times under specific load conditions, particularly for high-quality-factor resonant loads. To address these limitations, this paper proposes a hybrid islanding detection method that integrates AFD-based zero-time-interval perturbation with Pearson correlation analysis. The proposed approach introduces a controlled frequency drift in the inverter output current and evaluates the statistical correlation between the point of common coupling (PCC) frequency and its rate of change. By monitoring the dynamic relationship between these variables, the method reliably distinguishes islanding events from normal grid disturbances with enhanced sensitivity and reduced NDZ. The proposed technique is experimentally validated on a 350 W single-phase grid-connected PV system under IEEE Std. 929 and IEEE Std. 1547 islanding test conditions. Experimental results demonstrate detection times ranging from 0.09 s to 0.18 s across load quality factors of 0.5, 1.0, and 2.5, representing up to a 60% improvement compared to conventional AFD methods. In addition, the NDZ is reduced to below 5%, while inverter current total harmonic distortion remains below 2%, ensuring full compliance with grid interconnection standards. The proposed AFD–Pearson correlation–based method requires no additional hardware or communication infrastructure, making it a cost-effective, scalable, and practical solution for anti-islanding protection in modern grid-connected PV systems. Anti-Islanding PV Systems Pearson Correlation Active Frequency Drift Non-Detection Zone Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 29 Mar, 2026 Reviews received at journal 29 Mar, 2026 Reviewers agreed at journal 29 Mar, 2026 Reviews received at journal 01 Mar, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviews received at journal 23 Feb, 2026 Reviewers agreed at journal 19 Feb, 2026 Reviewers agreed at journal 19 Feb, 2026 Reviewers invited by journal 19 Feb, 2026 Editor invited by journal 19 Feb, 2026 Editor assigned by journal 17 Feb, 2026 Submission checks completed at journal 16 Feb, 2026 First submitted to journal 16 Feb, 2026 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-8777575","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594044343,"identity":"d30ea52a-dc66-4998-a368-308961e3839c","order_by":0,"name":"Ahmed G. 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Conventional Active Frequency Drift (AFD)\u0026ndash;based techniques, although effective, suffer from relatively large non-detection zones (NDZs) and prolonged detection times under specific load conditions, particularly for high-quality-factor resonant loads. To address these limitations, this paper proposes a hybrid islanding detection method that integrates AFD-based zero-time-interval perturbation with Pearson correlation analysis. The proposed approach introduces a controlled frequency drift in the inverter output current and evaluates the statistical correlation between the point of common coupling (PCC) frequency and its rate of change. By monitoring the dynamic relationship between these variables, the method reliably distinguishes islanding events from normal grid disturbances with enhanced sensitivity and reduced NDZ. The proposed technique is experimentally validated on a 350 W single-phase grid-connected PV system under IEEE Std. 929 and IEEE Std. 1547 islanding test conditions. Experimental results demonstrate detection times ranging from 0.09 s to 0.18 s across load quality factors of 0.5, 1.0, and 2.5, representing up to a 60% improvement compared to conventional AFD methods. In addition, the NDZ is reduced to below 5%, while inverter current total harmonic distortion remains below 2%, ensuring full compliance with grid interconnection standards. The proposed AFD\u0026ndash;Pearson correlation\u0026ndash;based method requires no additional hardware or communication infrastructure, making it a cost-effective, scalable, and practical solution for anti-islanding protection in modern grid-connected PV systems.\u003c/p\u003e","manuscriptTitle":"A Hybrid Active Frequency Drift and Pearson Correlation Method for Islanding Detection in Grid-Connected Photovoltaic Systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 05:42:45","doi":"10.21203/rs.3.rs-8777575/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"279696028048241403907485182330366439736","date":"2026-03-29T20:53:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T15:10:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318192278547384918035606048756633860044","date":"2026-03-29T14:59:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-02T03:55:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"311056121414609688683075448787248584029","date":"2026-02-24T10:35:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-23T18:17:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37445615512412810334067024588634985044","date":"2026-02-19T16:55:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185498627299482826863045969374027248756","date":"2026-02-19T08:55:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-19T08:30:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-19T06:55:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-17T12:04:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-16T15:23:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Applied Sciences","date":"2026-02-16T15:18:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-applied-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Applied Sciences](https://link.springer.com/journal/42452)","snPcode":"42452","submissionUrl":"https://submission.springernature.com/new-submission/42452/3","title":"Discover Applied Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"040ccbee-9f0c-43e3-b6e5-6f97280fea94","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T05:42:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 05:42:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8777575","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8777575","identity":"rs-8777575","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}