Voltage Collapse Prediction and Control of a Power System Using Classical Probability Theory

Voltage Collapse Prediction and Control of a Power System Using Classical Probability Theory | 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 Voltage Collapse Prediction and Control of a Power System Using Classical Probability Theory O. F. Amakiri, J. N. Onah, G. Ofualagba This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7628646/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract The incessant voltage collapse incidences on the Nigeria National grid is a serious concern. The primary dependability issue of voltage collapse makes it difficult to operate a reliable and secure power system network. This paper provides a comparative analysis of voltage stability approach and proposes a Bayesian approach for voltage collapse prediction. Voltage collapse indices, such as the line voltage stability indices (Lmm), fast voltage stability indices (FVSI), line reactive power indices (LQP), new line voltage stability indices (NLVSI), and modern voltage stability indices (MVSI), were explored. A Bayesian approach is then used to owing to the fact that it provides a more comprehensive assessment of the bus voltage's stability. It also provides a framework for updating presumptions on the stability of the system in light of data that has been observed. The 50-bus, 330kV Nigerian national grid test systems' voltage stability was evaluated using VSI with Bayesian techniques, and the weak and important buses were identified. Bus 50 (Jos) has the most critical value, 0.68 p.u., indicating marginal stability, whereas Bus 35 (Delta) has the lowest MVSI value, 0.61 p.u., and is categorized as critical. In contrast, the 50-bus system's weaker buses, such as Guaan's Bus 28 and Kano's Bus 44, show greater voltage stability index values between 0.75 and 0.80 p.u., indicating mild voltage instability without an immediate risk of collapse. Application of the Bayesian approach improves the critical buses from 0.61 to 0.898pu. When DPFC FACTS controller is being applied to weak and critical buses, the Lmn, FVSI, LQP, and NLSI with Bayesian algorithm were improved from 0.528 to 0.80pu and when IPFC was used it increases the weak bus from 0.66–0.97pu. Owing to the fact that DPFC outperforms IPFC for voltage enhancement, it was proposed for the voltage control. Voltage Collapse Bayesian algorithm DPFC IPFC Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Nov, 2025 Reviews received at journal 01 Nov, 2025 Reviewers agreed at journal 30 Oct, 2025 Reviews received at journal 23 Oct, 2025 Reviewers agreed at journal 22 Oct, 2025 Reviewers agreed at journal 15 Oct, 2025 Reviewers invited by journal 14 Oct, 2025 Editor invited by journal 13 Oct, 2025 Editor assigned by journal 08 Oct, 2025 Submission checks completed at journal 08 Oct, 2025 First submitted to journal 16 Sep, 2025 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-7628646","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":533760906,"identity":"3cfabb74-ea76-4aef-9112-c9e931ef50c7","order_by":0,"name":"O. F. 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The primary dependability issue of voltage collapse makes it difficult to operate a reliable and secure power system network. This paper provides a comparative analysis of voltage stability approach and proposes a Bayesian approach for voltage collapse prediction. Voltage collapse indices, such as the line voltage stability indices (Lmm), fast voltage stability indices (FVSI), line reactive power indices (LQP), new line voltage stability indices (NLVSI), and modern voltage stability indices (MVSI), were explored. A Bayesian approach is then used to owing to the fact that it provides a more comprehensive assessment of the bus voltage's stability. It also provides a framework for updating presumptions on the stability of the system in light of data that has been observed. The 50-bus, 330kV Nigerian national grid test systems' voltage stability was evaluated using VSI with Bayesian techniques, and the weak and important buses were identified. Bus 50 (Jos) has the most critical value, 0.68 p.u., indicating marginal stability, whereas Bus 35 (Delta) has the lowest MVSI value, 0.61 p.u., and is categorized as critical. In contrast, the 50-bus system's weaker buses, such as Guaan's Bus 28 and Kano's Bus 44, show greater voltage stability index values between 0.75 and 0.80 p.u., indicating mild voltage instability without an immediate risk of collapse. Application of the Bayesian approach improves the critical buses from 0.61 to 0.898pu. When DPFC FACTS controller is being applied to weak and critical buses, the Lmn, FVSI, LQP, and NLSI with Bayesian algorithm were improved from 0.528 to 0.80pu and when IPFC was used it increases the weak bus from 0.66\u0026ndash;0.97pu. 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