Particle swarm optimized power grid frequency stability control scheme in the presence of wind energy sources

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dc.contributor.author Chepkania, Terry L.
dc.contributor.author Musau, Peter M.
dc.contributor.author Wekesa, Cyrus W.
dc.date.accessioned 2023-03-17T09:42:22Z
dc.date.available 2023-03-17T09:42:22Z
dc.date.issued 2020
dc.identifier.citation 2020 IEEE PES/IAS PowerAfrica en_US
dc.identifier.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9219880
dc.identifier.uri http://repository.seku.ac.ke/handle/123456789/7206
dc.description DOI: 10.1109/PowerAfrica49420.2020.9219880 en_US
dc.description.abstract Renewable 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.iso en en_US
dc.publisher IEEE en_US
dc.subject Frequency instability en_US
dc.subject system inertia en_US
dc.subject particle swarm optimization en_US
dc.title Particle swarm optimized power grid frequency stability control scheme in the presence of wind energy sources en_US
dc.type Article en_US


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