Active Power Control Of Wind Farm Integration To Grid With Flywheel Energy Storage System Considering Wind Power Prediction

With large-scale wind power integration into grid, the fluctuation of active power output of wind farm will become a big challenge for safe and stable operation of the power system. The influence of large-scale wind power integration on system power balance is a main area in research. In light of this issue, implement wind power prediction and study the appropriate active power control method of the wind farm will contribute to improve the schedulability of wind farm and avoid the adverse impact on system power balance due to the output fluctuation of wind farm.The paper was based on the research object of a wind farm in the respect of wind power prediction. First, wind farm data preprocessing algorithm was proposed according to the Function Specification of Wind Power Prediction System. The bad data of wind farm source data was amended. Second, a short-term prediction model based on BP neural network was established, which provided96-points active predicted power curve of wind farm after prediction time was confirmed; Meanwhile, an ultrashort-term prediction model based on time-series algorithm was established, which provided rolling prediction curve of15minutes in advance of wind farm. The effectiveness of the wind power prediction algorithm was verified in MATLB. Based on this, the function and framework of corresponding wind power prediction system (WPPS) was designed. The WPPS was tested by the historical data from wind farm and it’s shown that the WPPS could work reliably. In the respect of active power control of wind farm, flywheel energy storage system (FESS) was connected to AC side of the doubly-fed induction generator (DFIG) wind farm. Anew smooth control strategy to level the wind power fluctuation was studied. It was demonstrated by quantitative analysis of simulation results that the proposed control strategy can track predicted power of wind farm and smooth the small active power fluctuation of wind farm effectively.