A Novel Hybrid Ant Colony-Particle Swarm Optimization Techniques Based Tuning STATCOM for Grid Code Compliance

dc.contributor.authorTon, Duc Do
dc.contributor.authorKamel, Omar Makram
dc.contributor.authorDiab, Ahmed A. Zaki
dc.contributor.authorMossa, Mahmoud A.
dc.date.accessioned2020-05-12T10:03:50Z
dc.date.available2020-05-12T10:03:50Z
dc.date.issued2020-02-27
dc.description.abstractIntegrating wind power plants (WPPs) into power systems are increasing dramatically now a day. However, the dynamic performance of power systems will be affected by the large penetration level of such renewable sources of energy. From this context power system operators and transmission system operators have put regulation rules to keep pushing wind power plants to safeguard limits that keep power system more stable and reliable. One of these rules is providing a low voltage ride through (LVRT) for wind farms without disconnecting it from the power system. The current paper implements the STATCOM as a LVRT for a 9 MW wind farm connected to the grid through transmission system of 120 kV. For enhancing the dynamic performance of STATCOM, two types of optimization methodologies: ant colony (ACO) and particle swarm optimization (PSO), are proposed to fine tune the coefficients of PI controllers to optimally manage the STATCOM dynamics.en_US
dc.identifier.citationKamel, O. M., Diab, A. A. Z., Do, T. D., & Mossa, M. A. (2020). A Novel Hybrid Ant Colony-Particle Swarm Optimization Techniques Based Tuning STATCOM for Grid Code Compliance. IEEE Access, 8, 41566-41587.en_US
dc.identifier.uri10.1109/ACCESS.2020.2976828
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/4655
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.titleA Novel Hybrid Ant Colony-Particle Swarm Optimization Techniques Based Tuning STATCOM for Grid Code Complianceen_US
dc.typeArticleen_US
workflow.import.sourcescience

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