Please use this identifier to cite or link to this item:
https://repository.seku.ac.ke/handle/123456789/7206| Title: | Particle swarm optimized power grid frequency stability control scheme in the presence of wind energy sources |
| Authors: | Chepkania, Terry L. Musau, Peter M. Wekesa, Cyrus W. |
| Keywords: | Frequency instability system inertia particle swarm optimization |
| Issue Date: | 2020 |
| Publisher: | IEEE |
| Citation: | 2020 IEEE PES/IAS PowerAfrica |
| 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. |
| Description: | DOI: 10.1109/PowerAfrica49420.2020.9219880 |
| URI: | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9219880 http://repository.seku.ac.ke/handle/123456789/7206 |
| Appears in Collections: | School of Engineering and Technology (CS) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Chepkania_Particle swarm optimized....pdf | fulltext | 332.87 kB | Adobe PDF | ![]() View/Open |
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