Improved Frequency Stability in Autonomous AC Microgrids through Modified Whale Optimization Algorithm-Based PID Controllers

Improved Frequency Stability in Autonomous AC Microgrids through Modified Whale Optimization Algorithm-Based PID Controllers | 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 Article Improved Frequency Stability in Autonomous AC Microgrids through Modified Whale Optimization Algorithm-Based PID Controllers Monalisa Mohanty, Sujit Kumar Bhuyan, Niranjan Nayak, S. Purushotham, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6238162/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 integration of naturally replenished sources (NRS) has hastened micro grid development, owing to environmental concerns and rising electrical demand. This study looks at the modelling and control of a self-governing AC micro grid that includes solar thermal power generation, wind turbines, tidal power generation, micro-turbines, biomass, diesel engines, and energy storage devices. Load frequency control (LFC) is critical for ensuring frequency stability by balancing generation and demand, reducing frequency variations. To improve LFC, this study substitutes traditional approaches with metaheuristic-optimized control. The Whale Optimisation Algorithm (WOA) is a relatively new swarm intelligence optimisation technique that is employed in a variety of scientific and engineering disciplines. This work presents a modified WOA, known as MWOA, to solve the original algorithm's slow convergence, tendency to stagnate at local minima, and poor stability. The changes include using a tent map function to optimise initial population distribution, new iteration-based strategies for updating the convergence factor and inertia weight to balance global and local searches, and an ideal feedback strategy to improve global search performance. MATLAB and OPAL-RT simulations show that MWOA-optimized controllers outperform in terms of performance and precision, representing a breakthrough in micro grid frequency stability and demonstrating their suitability for real-world power systems. Physical sciences/Engineering/Electrical and electronic engineering Physical sciences/Energy science and technology/Energy storage Physical sciences/Energy science and technology/Renewable energy Micro grid (MG) Proportional-Integrator-Derivative (PID) Integral of squared error (ISE) Modified Whale Optimisation Algorithm (MWOA) Opal-RT Matlab-2019b 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. 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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-6238162","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":460350934,"identity":"650ff54c-bea5-477f-820b-a620fb53965c","order_by":0,"name":"Monalisa Mohanty","email":"","orcid":"","institution":"SOA University","correspondingAuthor":false,"prefix":"","firstName":"Monalisa","middleName":"","lastName":"Mohanty","suffix":""},{"id":460350935,"identity":"0c4ff278-c9d9-432e-bd02-cca68d88d7f4","order_by":1,"name":"Sujit Kumar Bhuyan","email":"","orcid":"","institution":"Manikaran Analytics Limited","correspondingAuthor":false,"prefix":"","firstName":"Sujit","middleName":"Kumar","lastName":"Bhuyan","suffix":""},{"id":460350936,"identity":"2e8ce7c7-889b-4c7b-b207-fdb71ff1ccd0","order_by":2,"name":"Niranjan Nayak","email":"","orcid":"","institution":"SOA University","correspondingAuthor":false,"prefix":"","firstName":"Niranjan","middleName":"","lastName":"Nayak","suffix":""},{"id":460350937,"identity":"168f0827-33ed-467a-ab52-829586c3c4c9","order_by":3,"name":"S. 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