Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6766610 | Renewable Energy | 2016 | 8 Pages |
Abstract
Results showed that power variations depended on distinctive wind regimes and the number of turbines. Ngong (25Â MW) power was evenly distributed between 0 and 100%; Kinangop (60Â MW) was concentrated between 20 and 60% and Turkana (300Â MW) between 20 and 80% of their respective peak values. The standard deviations reduced as farm capacity increased due to the turbine smoothing effect. The reserve requirements increased on average, 30Â MW per percentage wind integration. The combined Ngong/Turkana (325Â MW) reserve requirements were less than for Ngong/Kinangop (85Â MW), indicating the significance of site correlations. . Also, when Ngong was up-scaled to the same output level as the three interconnected sites (385Â MW) reserve requirement increases by 25.5%, thus indicating the importance of geographical spread.
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Maulidi Barasa, Alex Aganda,