A robust crow search algorithm based power system state estimation

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dc.authoridAndiç, Cenk/0000-0003-1123-899Xen_US
dc.authorscopusid57818691400en_US
dc.authorscopusid35103037800en_US
dc.authorscopusid8307948200en_US
dc.authorwosidAndiç, Cenk/AEL-6941-2022en_US
dc.contributor.authorAndic, Cenk
dc.contributor.authorOzturk, Ali
dc.contributor.authorTurkay, Belgin
dc.date.accessioned2024-08-23T16:04:50Z
dc.date.available2024-08-23T16:04:50Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description7th International Conference on Renewable Energy and Conservation (ICREC) -- NOV 18-20, 2022 -- Paris, FRANCEen_US
dc.description.abstractThe State Estimation (SE) computational procedure plays a crucial role in modern electric power system security control by monitoring and analyzing operational conditions and predicting any emergency. In order to estimate state variables, Power System State Estimation (PSSE) takes into account the magnitudes and phases of voltage on each bus. To address the state estimation challenges in power systems, in this paper, we propose a novel application of the Crow Search Algorithm (CSA) specifically tailored for the state estimation problem. We have assessed the introduced algorithm using the frameworks of both the IEEE 14-bus and IEEE 30-bus test systems. The first formulation is the Weighted Least Square (WLS) method, and the second is the Weighted Least Absolute Value (WLAV) method, both of which are objective function formulations. By comparing the results, it is clear that CSA-based SE is superior to the other metaheuristic algorithms considered, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Artificial Bee Swarm Optimization (ABSO). As a point of comparison, we use the Newton-Raphson method for calculating load flow. It has been shown that the proposed CSA-based SE technique has better accuracy than the other two algorithms in all different test systems. With this study, the power system is operated more accurately and reliably by the operators operating the system. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Peer-review under responsibility of the scientific committee of the 2022 7th International Conference on Renewable Energy and Conservation, ICREC, 2022.en_US
dc.identifier.doi10.1016/j.egyr.2023.09.075
dc.identifier.endpage501en_US
dc.identifier.issn2352-4847
dc.identifier.scopus2-s2.0-85171626294en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage490en_US
dc.identifier.urihttps://doi.org/10.1016/j.egyr.2023.09.075
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14384
dc.identifier.volume9en_US
dc.identifier.wosWOS:001124191100068en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofEnergy Reportsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCrow search algorithmen_US
dc.subjectPower systemsen_US
dc.subjectState estimationen_US
dc.subjectUtilizing Scadaen_US
dc.subjectIdentificationen_US
dc.titleA robust crow search algorithm based power system state estimationen_US
dc.typeConference Objecten_US

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