Blockchain Intelligence Empowered Uncertainty Management in IoT Assisted Smart Grids

Blockchain Intelligence Empowered Uncertainty Management in IoT Assisted Smart Grids | 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 Blockchain Intelligence Empowered Uncertainty Management in IoT Assisted Smart Grids Tamizharasi GS, Arjun K P, R. Sathiyaraj, Achyut Shankar, Patrick Siarry This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4448342/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 recent advances in renewable energy sources impose an urgent need on global community to find an alternative measure for climate-unfriendly fossil fuels. As a result, the energy flow across smart grids has become bidirectional that requires greater attention. Despite the increasing advantages of smart grid application, it deals with greater challenges in managing the supply and demand of power sources. This is because of the reason that power generation, distribution and consumption across smart grids are highly complex. Since all these processes are time-dependent, dynamic management of grid stability has become a significant requirement. Most existing systems adopt a distributed system with a central authority to solve this problem. Such systems are more prone to various security attacks and become a single point of failure in many cases. This paper proposes a blockchain-based decentralized multiparty learning system to ensure smart grid stability with enhanced security and efficiency measures. The experimental observations are made with a power grid simulation dataset taken from Kaggle. From the experiment, it is observed that the proposed approach takes an average of 25ms to read the data across the block, and it takes around 4s to generate a new block. Further with respect to the addition of more intelligent terminals, the proposed approach consumes only 70% of the energy required by conventional methods to perform the task. The prediction and classification accuracy of the proposed system is also analyzed, and it shows 98% accuracy. Blockchain Internet of Things smart grids energy consumption energy management security attacks 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-4448342","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":305183536,"identity":"9cb6491a-77ae-4832-a8d1-5a811b0a7c05","order_by":0,"name":"Tamizharasi GS","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYHAC5gcJBjY8/OztBx8AeTx8ROhgM/hQkSYj2XMm2QCkhY0ILQySM84ctjG4kWAmAeIT1CLvf/6AMW/bYR6glrTKrzl2MmwMzA8f3cCjxfBGMsNj3rZ0HskzD4/dlt2WDHQYm7FxDj4tM5gZgLZY8/AdT0i7LbmNGaiFh00ar5b+wwzSvG3MPAwHEsyKJbfVE9Yiz5AM8r4zj8CJBDPGj9sOE9ZiIJFsBgpkHlAgSzNuO87DxkzAL/L9Bx+DotIeFJUff26rBjKaHz7Ga8sBJA7QRyASj3KwLQ1IHMYfBFSPglEwCkbByAQA6yhH2T9bBSkAAAAASUVORK5CYII=","orcid":"","institution":"CMR University","correspondingAuthor":true,"prefix":"","firstName":"Tamizharasi","middleName":"","lastName":"GS","suffix":""},{"id":305183537,"identity":"c2072290-79e3-4952-ab97-e2eb0b92e0f4","order_by":1,"name":"Arjun K P","email":"","orcid":"","institution":"GITAM University","correspondingAuthor":false,"prefix":"","firstName":"Arjun","middleName":"K","lastName":"P","suffix":""},{"id":305183538,"identity":"ae18b30a-a512-4e3f-b2b8-e2269ac6b548","order_by":2,"name":"R. 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