Please use this identifier to cite or link to this item: https://repository.seku.ac.ke/handle/123456789/7206
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dc.contributor.authorChepkania, Terry L.-
dc.contributor.authorMusau, Peter M.-
dc.contributor.authorWekesa, Cyrus W.-
dc.date.accessioned2023-03-17T09:42:22Z-
dc.date.available2023-03-17T09:42:22Z-
dc.date.issued2020-
dc.identifier.citation2020 IEEE PES/IAS PowerAfricaen_US
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9219880-
dc.identifier.urihttp://repository.seku.ac.ke/handle/123456789/7206-
dc.descriptionDOI: 10.1109/PowerAfrica49420.2020.9219880en_US
dc.description.abstractRenewable energy sources (RES) have become a subject of interest world-wide, including in Kenya where recently a 310 MW Wind Power plant was commissioned. They are clean energy technologies and relatively cheaper compared to fossil-fuels. They do not inherently provide system inertia from rotating masses of the rotor of the wind turbine hence when integrated into the grid pose electrical power system frequency instability. The optimization and load flow were conducted using particle swarm optimization algorithm and Newton Raphson algorithm. Results showed that the voltage profile and frequency response profile improved significantly as the percentage of wind penetration increased in the grid. For the test system considered, the maximum wind penetration was 32.1%. Notably, as the percentage of wind penetration increased, the rate of change of frequency worsened because of the intermittent nature of wind energy source.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectFrequency instabilityen_US
dc.subjectsystem inertiaen_US
dc.subjectparticle swarm optimizationen_US
dc.titleParticle swarm optimized power grid frequency stability control scheme in the presence of wind energy sourcesen_US
dc.typeArticleen_US
Appears in Collections:School of Engineering and Technology (CS)

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