Optimal Allocations of Wind Turbines in Power Systems Using Artificial Rabbits Optimization Technique

Optimal Allocations of Wind Turbines in Power Systems Using Artificial Rabbits Optimization Technique | 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 Optimal Allocations of Wind Turbines in Power Systems Using Artificial Rabbits Optimization Technique A. A. Abou El-Ela, M. K. Ali, A. F. Nasef, R. A. Amer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3896817/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 Wind Energy Conversion Systems (WECS) is one of the burning research fields these days. Governments encourage researchers and planners to make plans towardincreasing the amount of power generation from renewable energy sources (RES) in the future because conventional energy sources will cause a crisis for the environment. The installationof WECS units can cause an adverse effect if they are notproperly allocated. Therefore, this paper presents the applications of modern optimization techniques such as the artificial rabbit optimization algorithm (ARO), the grey wolfoptimizer (GWO), and particle swarm optimization (PSO) for determining the optimal location and sizing of WECS. The effectiveness of these techniques is demonstrated with IEEE 14-bus and IEEE 30-bus considering various penetration conditions. Also, the effect of wind turbines on system transient performance is investigated using robust non-linear models ofboth synchronous machines and wind turbine generators whenthe system is exposed to a symmetrical three-phase short circuitfault. The results show the ability of the ARO algorithm compared to both GWO and PSO techniques in solving thewind turbine generator (WTG) placement and sizing problem.The result show that ARO-based WTG increases the stability ofthe power system, improves the voltage profile, reduces bothactive and reactive power losses in the systems, and enhances dynamics performance for the overall systems. All the simulations of the system models are carried out using MATLAB/SIMULINK and given in the form of comparative results with a three-phase short circuit, and changes in wind penetration level to show the stability of the system. RES ARO GWO PSO WTG Wind Energy Conversion Systems 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-3896817","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269240645,"identity":"0a67746e-3cef-4b40-921c-85ef1c320bd7","order_by":0,"name":"A. A. Abou El-Ela","email":"","orcid":"","institution":"Menoufia University","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"A. Abou","lastName":"El-Ela","suffix":""},{"id":269240646,"identity":"a61ad68f-4f7f-4671-a04c-72d0313b5b76","order_by":1,"name":"M. K. 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Governments encourage researchers and planners to make plans towardincreasing the amount of power generation from renewable energy sources (RES) in the future because conventional energy sources will cause a crisis for the environment. The installationof WECS units can cause an adverse effect if they are notproperly allocated. Therefore, this paper presents the applications of modern optimization techniques such as the artificial rabbit optimization algorithm (ARO), the grey wolfoptimizer (GWO), and particle swarm optimization (PSO) for determining the optimal location and sizing of WECS. The effectiveness of these techniques is demonstrated with IEEE 14-bus and IEEE 30-bus considering various penetration conditions. Also, the effect of wind turbines on system transient performance is investigated using robust non-linear models ofboth synchronous machines and wind turbine generators whenthe system is exposed to a symmetrical three-phase short circuitfault. 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