Active power control of wind power considering power forecasting error

Abstract

The power control can not meet the control target due to the prediction error of wind power generation. Based on the difference of power prediction error and confidence interval between different new energy power stations, an optimal control strategy for active power of wind farms was proposed. The strategy used historical data to evaluate the prediction error distribution and confidence interval of wind power, and introduced confidence interval constraints to establish a wind power active optimization model to realize active power distribution, so as to realize the complementary prediction errors among wind farms with asymmetric error distribution. Combined with the actual data of a wind power based in a province in China, a simulation example was designed to verify the rationality and effectiveness of the proposed strategy. The results show that the proposed method can effectively improve the control performance of wind power active power, and the control deviation in the simulation example can be reduced by about 10%, which is helpful to reduce the risk of wind power active power control deficiency.

Keywords

• wind power generation
• confidence interval
• active power control
• power forecas