A Comprehensive Framework for Evaluating and Predicting Investment Risks in Renewable Energy Projects: A Case Study of Maynak Hydropower Station

A Comprehensive Framework for Evaluating and Predicting Investment Risks in Renewable Energy Projects: A Case Study of Maynak Hydropower Station | 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 Comprehensive Framework for Evaluating and Predicting Investment Risks in Renewable Energy Projects: A Case Study of Maynak Hydropower Station Nanjie Xu, Anxia Wan, Yue Li, Ehsan Elahi, Benhong Peng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3666924/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 study introduces a holistic analysis framework designed to evaluate and predict the investment risks associated with foreign renewable energy initiatives. The primary objective of this framework is to address the inherent uncertainties that often accompany such projects. To achieve this, we employ the variable weight matter-element extension model to establish the project's fundamental reliability function. Subsequently, we enhance this model using evidence theory to determine the project's risk level and generate risk index measurement results. Additionally, we utilize the GM model for forecasting future project risks. To illustrate the practicality of our approach, we provide a case study focused on the risk assessment and prediction for the Maynak Hydropower Station. Our findings indicate that during 2008, 2014, 2020, and 2022, the project faced a high level of investment risk. Key risk indicators included political instability, policy changes, legislative gaps, cultural risks, exchange rate fluctuations, technical challenges, and management risks. Moreover, from 2023 to 2027, the project's investment risk level moderated, with risk measurement results aligning closely with actual circumstances, thus validating the efficacy and applicability of our model. Extension model Evidence theory Risk assessment GM model Risk prediction Full Text 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-3666924","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268318139,"identity":"35a59037-9838-4a58-b7a9-6c4c00abb20a","order_by":0,"name":"Nanjie Xu","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0005-7252-4385","institution":"Nanjing University of Information Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Nanjie","middleName":"","lastName":"Xu","suffix":""},{"id":268318140,"identity":"752af47c-1eee-4903-ad21-a63a6c918850","order_by":1,"name":"Anxia Wan","email":"","orcid":"","institution":"NUIST: Nanjing University of Information Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Anxia","middleName":"","lastName":"Wan","suffix":""},{"id":268318141,"identity":"c2f2da59-7ff6-416c-9b53-91421d53d791","order_by":2,"name":"Yue Li","email":"","orcid":"","institution":"NUIST: Nanjing University of Information Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Li","suffix":""},{"id":268318142,"identity":"4a56b811-cc83-48be-b8ef-0bfc195b47c0","order_by":3,"name":"Ehsan Elahi","email":"","orcid":"","institution":"Shandong University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Ehsan","middleName":"","lastName":"Elahi","suffix":""},{"id":268318143,"identity":"ff5a0814-89fa-407e-9ca7-e13351a83a1b","order_by":4,"name":"Benhong Peng","email":"","orcid":"https://orcid.org/0000-0002-8624-1782","institution":"NUIST: Nanjing University of Information Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Benhong","middleName":"","lastName":"Peng","suffix":""}],"badges":[],"createdAt":"2023-11-26 10:10:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3666924/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3666924/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51589270,"identity":"e8e12feb-9903-43e7-b8aa-92e07ed6bd24","added_by":"auto","created_at":"2024-02-24 16:43:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":622014,"visible":true,"origin":"","legend":"","description":"","filename":"manuscriptDA.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3666924/v1_covered_0aafa46f-15d4-4077-82d3-04e6dffb3693.pdf"}],"financialInterests":"","formattedTitle":"A Comprehensive Framework for Evaluating and Predicting Investment Risks in Renewable Energy Projects: A Case Study of Maynak Hydropower Station","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":"Extension model, Evidence theory, Risk assessment, GM model, Risk prediction","lastPublishedDoi":"10.21203/rs.3.rs-3666924/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3666924/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study introduces a holistic analysis framework designed to evaluate and predict the investment risks associated with foreign renewable energy initiatives. 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