Construction of a Sustainable Development-Oriented Business Evaluation System for New-Type Power Systems

Construction of a Sustainable Development-Oriented Business Evaluation System for New-Type Power 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 Construction of a Sustainable Development-Oriented Business Evaluation System for New-Type Power Systems Xiaona Gao, Tinghao Lei, Xin Zhou, Xiaozhu Lin, Xiting Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6445360/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 The world-wide development of sustainable energy requires immediate expansion of new energy infrastructure through renewable energy technologies together with smart grids systems. Due to its multi-dimensional characteristics the industry proves hard to evaluate because environmental and social aspects merge with economic and technological considerations. The solution aims to develop an ML-based AI system for sustainable business evaluation which ranks new-type power system companies. The system provides decision-makers alongside investors and regulators with an integrated data-based solution which enables them to assess and analyze sustainability performances of these firms. The examination collects basic information from utilities through their environmental reports along with their financial performance indicators along with their technological innovation indicators and social benefit scores. Standardization combined with outlier handling measures serve as preprocessing techniques to assure that data remains of high quality. The process includes feature extraction together with linear Discriminant Analysis (LDA) for identifying essential sustainability performance indicators which include carbon offsetting measures along with energy efficiency metrics and scalability aspects. The scalable shuffled frog leaping algorithm-adapted logistic regression (SSFLA-LR) model serves well due to its data handling abilities of high dimensions and its output interpretability. The sustainability evaluation model using SSFLA-LR runs on Python 3.9 shows efficient results in identifying high sustainability potential companies through their displayed environmental and social and economic metrics. With 5-fold cross-validation SSFLA-LR yields accuracy of 94.0% and precision of 93.12% together with a recall of 94.40% and an F1 Score of 93.74%. The proposed AI evaluation method provides an effective method to analyze business enterprise performance in emerging power networks that drives sustainable development. New-type power systems sustainable development environmental impact business evaluation system scalable shuffled frog leaping algorithm tuned logistic regression (SSFLA-LR) 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-6445360","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":477438671,"identity":"0478b374-5b88-4310-8983-734fa3fbc56c","order_by":0,"name":"Xiaona Gao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYBACg8Ngyo6Bgb3/44MPQCYfAwMzMVqSGRh4DhgbzmBgkGAjpEWyAUwdAKp1MJPmIUYLPzvzw8cFNQfk+SUYko1tKg7XsbE3HzZgqLGJxqWFjZnN2HjGsQOGM2c3HHycc+awBBvPseQEhmNpuQ04tTAA3cN2nHHDnYPNxrltQC0SOcYHGBsO49TCz8z+TZrn32H7DTeS2aQtidEi2cxjJs3bdjhxw400NmlGqJYEfFoMDvMUG/P2JSfP7DnDbNhzJl2yDegXgwQ8fjE4f3zjY55vdrb97D2MD35UWPPzA0NM4kONDU4tOEACacpHwSgYBaNgFKABAKlIVOsv3hgyAAAAAElFTkSuQmCC","orcid":"","institution":"Zunyi Power Supply Bureau of Guizhou Power Grid Co., Ltd. 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