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Forecasting skills for a wind farm would significantly degrade if the complex wake effects of the upstream wind farms are excluded, especially when they are spatially close to each other. In this study, the Weather Research and Forecasting (WRF) model has been used to predict wind speed and power for a wind farm in Pakistan in the presence of wake interference from neighboring wind farms for two different seasons. Forecasting is done for two different cases i.e. without and with inter-farm wake effects, and different statistical error parameters were evaluated based on the real observations. A significant reduction in errors was observed in the latter case. For instance, the mean absolute errors in wind speed prediction were reduced by 7.7% and 14% in June (summer) and January (winter) respectively, by the inclusion of inter-farm wake effects. Similarly, an improved forecast of power output was obtained by incorporating the interaction of upstream wind farms i.e. a reduction of 15% and 26% in the normalized mean absolute error in power output values was observed for June and January, respectively. However, the prediction accuracy of power output substantially deteriorated in the winter season.
- Energy forecasting
- Mesoscale simulation
- Seasonal variation
- Wake interference
- Wind farm
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology
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- 1 Finished
Meso- & Microscale Layout Optimization of Commercial-Scale Wind Farms under Intra- and Inter-Farm Wake Interferences
1/01/19 → 30/11/21