Bias-correction method for wind-speed forecasting

The improvement in wind-speed-forecast accuracy by modifying the bias between simulations and observations can significantly improve the wind-power efficiency of wind farms, increase grid stability, relieve grid pressure, and reduce economic costs. Gansu (China) is rich in wind-energy resources and has a large number of wind farms, but there are also difficulties in the simulation of the wind speed. While the correlation co-efficient between the simulated wind speed and that observed is high, the bias is large, making it necessary for a fast cyclic-bias correction method based on historical data. This new bias-correction method uses three parameters (average, variance trend) to correct the simulated wind speed. The results show that the bias is reduced to 1-2 m/s from 2-3 m/s, which meets the forecasting demands of wind-farm operators. The percentage wind-speed biases of the different wind farms are also reduced by 17 % to 23 %.