Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93965
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dc.contributorDepartment of Electrical Engineeringen_US
dc.creatorXia, SWen_US
dc.creatorBu, SQen_US
dc.creatorZhang, Xen_US
dc.creatorXu, Yen_US
dc.creatorZhou, Ben_US
dc.creatorZhu, JBen_US
dc.date.accessioned2022-08-03T08:49:34Z-
dc.date.available2022-08-03T08:49:34Z-
dc.identifier.issn0306-2619en_US
dc.identifier.urihttp://hdl.handle.net/10397/93965-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2018 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Xia, S. W., Bu, S. Q., Zhang, X., Xu, Y., Zhou, B., & Zhu, J. B. (2018). Model reduction strategy of doubly-fed induction generator-based wind farms for power system small-signal rotor angle stability analysis. Applied energy, 222, 608-620 is available at https://doi.org/10.1016/j.apenergy.2018.04.024.en_US
dc.subjectComputational efficiencyen_US
dc.subjectDamping torque contributionen_US
dc.subjectDynamic model componenten_US
dc.subjectReduced modelen_US
dc.subjectSmall-signal rotor angle stabilityen_US
dc.subjectWind energyen_US
dc.titleModel reduction strategy of doubly-fed induction generator-based wind farms for power system small-signal rotor angle stability analysisen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage608en_US
dc.identifier.epage620en_US
dc.identifier.volume222en_US
dc.identifier.doi10.1016/j.apenergy.2018.04.024en_US
dcterms.abstractFollowing the decarbonisation and decentralisation of energy industry, wind energy is becoming a promising generation source to reduce greenhouse emission, and meet future energy demand. Unlike traditional generation using synchronous generators, many wind turbines use induction generators, e.g., doubly-fed induction generators, due to the cost effective design of adjustable-speed operation and flexibility in reactive power control. However, a growing number of doubly-fed induction generator-based wind farms has significantly increased the complexity of system dynamic model, and hence increased the computational burden of power system dynamic study. This becomes a serious concern in the electricity system operation, where a fast power system stability assessment is required to assure the real-time system security during high levels of wind power penetration. In this paper, a novel model reduction strategy of doubly-fed induction generators is derived to improve the efficiency of power system dynamic study, while the study accuracy is still maintained to an acceptable level. To achieve this, a method to assess the modeling adequacy of doubly-fed induction generators for small-signal rotor angle stability analysis is firstly introduced. By evaluating the damping torque contribution to stability margin from different dynamic model components of doubly-fed induction generators, the proposed method provides a quantitative index (i.e., participation level) to show the involvement of each dynamic model component of doubly-fed induction generators in affecting power system damping, and thus can instruct how to reduce the model of doubly-fed induction generators in an efficient and accurate manner. On this basis, five model reduction plans and a model reduction strategy have been proposed according to the previously defined participation levels. The effectiveness of the proposed strategy is demonstrated in the New England test system and a real large power grid in Eastern China respectively. It has been proved that the proposed the model reduction strategy of doubly-fed induction generators for power system dynamic study is undoubtedly useful to the electricity system operator, with a key benefit in reducing model complexity and improving computational efficiency of a large-scale power system with an increasing number of wind power generation.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationApplied energy, 15 July 2018, v. 222, p. 608-620en_US
dcterms.isPartOfApplied energyen_US
dcterms.issued2018-07-15-
dc.identifier.scopus2-s2.0-85045472187-
dc.identifier.eissn1872-9118en_US
dc.description.validate202205 bchyen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberEE-0345-
dc.description.fundingSourceRGCen_US
dc.description.fundingTextThe Hong Kong Polytechnic University; Beijing Natural Science Foundation; Support Program for the Excellent Talents in Beijing Cityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6834878-
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