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Article: Applicability comparison of different algorithms for ambient signal based load model parameter identification

TitleApplicability comparison of different algorithms for ambient signal based load model parameter identification
Authors
KeywordsAmbient signal based load model parameter identification
Active-set algorithm
Differential evolution algorithm
Grid search algorithm
Interior-point algorithm
Issue Date2019
PublisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/locate/ijepes
Citation
International Journal of Electrical Power & Energy Systems, 2019, v. 111, p. 382-389 How to Cite?
AbstractThe time-varying characteristic of the power load can be tracked with the ambient signal based load model parameter identification method proposed recently. Meanwhile, the small fluctuations of the ambient signal bring higher requirement for optimization algorithm as well. The interior-point algorithm (IPA) and the activeset algorithm (ASA) are two typical traditional nonlinear constrained optimization algorithms, while the differential evolution algorithm (DEA) is an excellent heuristic search algorithm. Besides, the grid search algorithm (GSA) is a violent search algorithm, which is also an effective method considering the fact that the real load model parameters are unknown in practical power system. Based on the review of the basic idea of the four algorithms, the applicability of the four algorithms is comparatively assessed for ambient signal based load model parameter identification. Their performance is compared using ambient data from both simulation and field phasor measurement unit (PMU) in China Southern Power Grid considering the identification accuracy, calculation time, and the robustness to measurement error and algorithm parameters. Some general conclusions are drawn from the analysis for several cases.
Persistent Identifierhttp://hdl.handle.net/10722/273870
ISSN
2023 Impact Factor: 5.0
2023 SCImago Journal Rankings: 1.711
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWang, Y-
dc.contributor.authorLu, C-
dc.contributor.authorZhang, X-
dc.date.accessioned2019-08-18T14:50:17Z-
dc.date.available2019-08-18T14:50:17Z-
dc.date.issued2019-
dc.identifier.citationInternational Journal of Electrical Power & Energy Systems, 2019, v. 111, p. 382-389-
dc.identifier.issn0142-0615-
dc.identifier.urihttp://hdl.handle.net/10722/273870-
dc.description.abstractThe time-varying characteristic of the power load can be tracked with the ambient signal based load model parameter identification method proposed recently. Meanwhile, the small fluctuations of the ambient signal bring higher requirement for optimization algorithm as well. The interior-point algorithm (IPA) and the activeset algorithm (ASA) are two typical traditional nonlinear constrained optimization algorithms, while the differential evolution algorithm (DEA) is an excellent heuristic search algorithm. Besides, the grid search algorithm (GSA) is a violent search algorithm, which is also an effective method considering the fact that the real load model parameters are unknown in practical power system. Based on the review of the basic idea of the four algorithms, the applicability of the four algorithms is comparatively assessed for ambient signal based load model parameter identification. Their performance is compared using ambient data from both simulation and field phasor measurement unit (PMU) in China Southern Power Grid considering the identification accuracy, calculation time, and the robustness to measurement error and algorithm parameters. Some general conclusions are drawn from the analysis for several cases.-
dc.languageeng-
dc.publisherElsevier Ltd. The Journal's web site is located at http://www.elsevier.com/locate/ijepes-
dc.relation.ispartofInternational Journal of Electrical Power & Energy Systems-
dc.subjectAmbient signal based load model parameter identification-
dc.subjectActive-set algorithm-
dc.subjectDifferential evolution algorithm-
dc.subjectGrid search algorithm-
dc.subjectInterior-point algorithm-
dc.titleApplicability comparison of different algorithms for ambient signal based load model parameter identification-
dc.typeArticle-
dc.identifier.emailZhang, X: zhangxr7@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.ijepes.2019.03.061-
dc.identifier.scopuseid_2-s2.0-85064464210-
dc.identifier.hkuros302018-
dc.identifier.volume111-
dc.identifier.spage382-
dc.identifier.epage389-
dc.identifier.isiWOS:000470943700032-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0142-0615-

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