Optimal Power Flow Considering Global Voltage Stability Based on a Hybrid Modern Heuristic Technique

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dc.authoridBai, Wenlei/0000-0003-3759-3455
dc.authoridEKE, Ibrahim/0000-0003-4792-238X
dc.contributor.authorBai, Wenlei
dc.contributor.authorLee, Kwang Y.
dc.contributor.authorEke, İbrahim
dc.date.accessioned2025-01-21T16:33:04Z
dc.date.available2025-01-21T16:33:04Z
dc.date.issued2022
dc.departmentKırıkkale Üniversitesi
dc.description11th IFAC Symposium on Control of Power and Energy Systems (CPES) -- JUN 21-23, 2022 -- ELECTR NETWORK
dc.description.abstractIntegrating large renewable energy to grid complicates power systems' steady-state operation which leads to the high risk of voltage instability due to its intermittent and stochastic properties. The steady-state voltage stability margin (VSM) can be measured by the smallest singular value (SSV) of the load flow Jacobian matrix. Unlike other voltage stability indices such as L -index which shows the probability of voltage collapse for a particular bus, namely, local stability index, SSV represents the global voltage stability and the smaller the value is, the riskier the whole system's stability is. Voltage stability constrained -optimal power flow (VSC-OPF) is an effective tool to stabilize system voltage. Yet VSC-OPF is a highly non-linear and non-convex problem because of AC power flow and implicit SSV constraints. Such challenge is tackled, in this work, by a novel hybrid heuristic method, differential evolutionary particle swarm optimization (DEEPSO) which can easily formulate explicit constraints and objective functions to obtain near-optimal solutions efficiently. Several case studies are conducted on the IEEE 30 bus system, and they demonstrate the effectiveness of the hybrid technique and presents some insights on voltage profiles under various system operating condition. Copyright (C) 2022 The Authors.
dc.description.sponsorshipInt Federat Automat Control, Tech Comm 6 3 Power & Energy Syst,Int Federat Automat Control, Tech Comm 1 2 Adapt & Learning Syst,Int Federat Automat Control, Tech Comm 1 5 Networked Syst,Int Federat Automat Control, Tech Comm 5 4 Large Scale Complex Syst,Int Federat Automat Control, Tech Comm 6 4 Fault Detect, Supervis & Safety Tech Proc,Int Federat Automat Control, Tech Comm 7 4 Transportat Syst,Int Federat Automat Control, Tech Comm 9 1 Econ, Business, & Financial Syst,Int Federat Automat Control, Tech Comm 9 3 Control Smart Cities,Int Federat Automat Control
dc.identifier.doi10.1016/j.ifacol.2022.07.072
dc.identifier.endpage418
dc.identifier.issn2405-8963
dc.identifier.issue9
dc.identifier.scopus2-s2.0-85137165563
dc.identifier.scopusqualityQ3
dc.identifier.startpage413
dc.identifier.urihttps://doi.org/10.1016/j.ifacol.2022.07.072
dc.identifier.urihttps://hdl.handle.net/20.500.12587/23702
dc.identifier.volume55
dc.identifier.wosWOS:000857162300025
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofIfac Papersonline
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectGlobal voltage stability; Optimal power flow (OPF); Hybrid heuristic technique; Differential evolution (DE); Evolutionary particle swarm optimization (EPSO)
dc.titleOptimal Power Flow Considering Global Voltage Stability Based on a Hybrid Modern Heuristic Technique
dc.typeConference Object

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