Optimal Power Flow Based on a Metaheuristics Optimization Approach for the Iraqi Super High Voltages Network

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dc.authorid0009-0006-9824-5998
dc.authorid0000-0003-1164-7187
dc.contributor.authorAlmosawi, Ali
dc.contributor.authorÇevik, Mesut
dc.contributor.authorErsoy, Aysel
dc.date.accessioned2025-08-14T17:00:56Z
dc.date.available2025-08-14T17:00:56Z
dc.date.issued2025
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü
dc.description.abstractOptimal power flow is a tool It enables operators to run the system as efficiently as possible within specific limitations. Therefore, many tools have been developed to assist operators to make decisions for different objectives. The optimal power flow (OPF) problem is the most difficult and complex problem in power system analysis and design due to the nonlinearities and imposed constrains. OPF’s goal is to reduce generation costs and transmission losses. when the demand and generated power are balanced. In this work, the proposed approach uses genetic algorithm (GA) and camping the Hybrid Particle Swarm Optimization and Genetic algorithm (HPSO+GA) as an intelligent methods to perform optimal power flow. Cost functions that are defined and minimized in this work are the overall active losses and amount of required fuel. The viability of the suggested method is confirmed by comparing the results of the presented methodology With previous research results. Using the MATLAB platform, the best load flow technique was evaluated using data from the Iraqi 400 KV transmission network, which consists of 58 buses. Results document the viability of the proposed method in terms of less active losses and reduced fuel costs. Moreover, the proposed GA and HPSO+GA methods requires no iterations hence errors of solution divergence and initial conditions are omitted.
dc.identifier.citationAlmosawi, A. A., Cevik, B. M., & Ersoy, C. A. (2025). Optimal Power Flow Based on a Metaheuristics Optimization Approach for the Iraqi Super High Voltages Network. IEEE Access, 13, 106724-106735. 10.1109/ACCESS.2025.3578579
dc.identifier.doi10.1109/ACCESS.2025.3578579
dc.identifier.endpage106735
dc.identifier.issn2169-3536
dc.identifier.scopus2-s2.0-105008043722
dc.identifier.scopusqualityQ1
dc.identifier.startpage106724
dc.identifier.urihttps://hdl.handle.net/20.500.12939/5878
dc.identifier.volume13
dc.identifier.wosWOS:001515628100043
dc.identifier.wosqualityQ2
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorAlmosawi, Ali
dc.institutionauthorÇevik, Mesut
dc.institutionauthorid0009-0006-9824-5998
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofIEEE Access
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Öğrenci
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectFuel cost
dc.subjectgenetic algorithm (GA)
dc.subjecthybrid particle swarm optimization (HPSO)
dc.subjectoptimal power flow (OPF)
dc.subjectsystem losses
dc.titleOptimal Power Flow Based on a Metaheuristics Optimization Approach for the Iraqi Super High Voltages Network
dc.typeArticle

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