Dynamic economic dispatch problem in hybrid renewable based power systems using oppositional based chaotic honey badger algorithm

Dynamic economic dispatch problem in hybrid renewable based power systems using oppositional based chaotic honey badger 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 Dynamic economic dispatch problem in hybrid renewable based power systems using oppositional based chaotic honey badger algorithm Barun Mandal, Provas Kumar Roy, Chandan Paul This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4688036/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 In this work, the chaotic honey badger algorithm (OCHBA) based on oppositional theory is used for the investigation of the wind-solar-electric vehicle (EV)-thermal based dynamic economic dispatch (DED) problem. The co-generation of solar, wind and battery storage units is optimised by the suggested approach. A constrained nonlin-ear optimization problem with discrete and continuous variables that is non-convex on a large scale is used to simulate the DED. A more reliable and efficient DED algorithm is required for direct power system operators’ decision-making. In order to minimise generation costs and simultaneously meet different load needs, DED calculates the amount of electrical power that committed units in a power system will generate. The development, testing and comparison utilising the 10-unit and 15-unit benchmark systems show the viability and efficacy of the suggested approach. Moreover, the results demonstrate the potential of the suggested method as well as its reliability and efficacy in resolving the DED issue for the systems under consideration. The results of the proposed approach methodology is compared with several methods that have been published most recently and the suggested OCHBA approach is used in multiple test systems with complex solution spaces in order to demonstrate its effectiveness and benefits. The suggested approach’s functionality and performance are contrasted with the traditional techniques. The algorithm’s dependability and ease of implementation, even on highly complicated and non-convex situations, are demonstrated by its excellent results. Wind energy (WE) Solar energy (SE) Electric vehicles (EVs) Renewable energy source (RES) Honey badger algorithm (HBA) Oppositional based chaotic honey badger algorithm (OCHBA) Dynamic economic load dispatch (DELD) Chaotic maps Probability density functions (PDF) Oppositional based learning (OBL) 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-4688036","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":329448349,"identity":"0584b39d-358a-4966-997c-7ada1752ac62","order_by":0,"name":"Barun Mandal","email":"data:image/png;base64,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","orcid":"","institution":"Kalyani Government Engineering College","correspondingAuthor":true,"prefix":"","firstName":"Barun","middleName":"","lastName":"Mandal","suffix":""},{"id":329448350,"identity":"2fe35cf0-c641-4e8d-a6b9-6f58fb09776b","order_by":1,"name":"Provas Kumar Roy","email":"","orcid":"","institution":"Kalyani Government Engineering College","correspondingAuthor":false,"prefix":"","firstName":"Provas","middleName":"Kumar","lastName":"Roy","suffix":""},{"id":329448351,"identity":"5342ee94-152a-41a1-a508-2f5d2cd1e90a","order_by":2,"name":"Chandan Paul","email":"","orcid":"","institution":"Dr. B C Roy Engineering College","correspondingAuthor":false,"prefix":"","firstName":"Chandan","middleName":"","lastName":"Paul","suffix":""}],"badges":[],"createdAt":"2024-07-04 17:33:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4688036/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4688036/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95223053,"identity":"647b6915-fd14-4195-a585-cca863af533f","added_by":"auto","created_at":"2025-11-05 16:21:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":692058,"visible":true,"origin":"","legend":"","description":"","filename":"Barun1015DEDOCHBA16062024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4688036/v1_covered_1699f9c9-db29-4165-ab4c-a988230168bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dynamic economic dispatch problem in hybrid renewable based power systems using oppositional based chaotic honey badger algorithm","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":"Wind energy (WE), Solar energy (SE), Electric vehicles (EVs), Renewable energy source (RES), Honey badger algorithm (HBA), Oppositional based chaotic honey badger algorithm (OCHBA), Dynamic economic load dispatch (DELD), Chaotic maps, Probability density functions (PDF), Oppositional based learning (OBL)","lastPublishedDoi":"10.21203/rs.3.rs-4688036/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4688036/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In this work, the chaotic honey badger algorithm (OCHBA) based on oppositional theory is used for the investigation of the wind-solar-electric vehicle (EV)-thermal based dynamic economic dispatch (DED) problem. The co-generation of solar, wind and battery storage units is optimised by the suggested approach. A constrained nonlin-ear optimization problem with discrete and continuous variables that is non-convex on a large scale is used to simulate the DED. A more reliable and efficient DED algorithm is required for direct power system operators’ decision-making. In order to minimise generation costs and simultaneously meet different load needs, DED calculates the amount of electrical power that committed units in a power system will generate. The development, testing and comparison utilising the 10-unit and 15-unit benchmark systems show the viability and efficacy of the suggested approach. Moreover, the results demonstrate the potential of the suggested method as well as its reliability and efficacy in resolving the DED issue for the systems under consideration. 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