Flywheel energy storage controlled by model predictive control to achieve smooth short-term high-frequency wind power

Abstract

The use of energy storage systems to improve the fluctuation of wind power generation has garnered significant in the development of wind power. However, the fluctuation of the signals in the high-frequency part of the wind turbine output is particularly drastic and short in duration. As a kind of physical energy storage device, the flywheel energy storage device has a fast response speed but higher requirements on the control system. In order to improve the control effect of the flywheel energy storage device, the model predictive control algorithm is improved in this paper. First, the high-frequency components of the wind farm output power data are extracted by the wavelet packet decomposition algorithm, and the high-frequency components are optimized by mathematical interpolation as the data basis. Secondly, a mathematical model of the flywheel energy storage system applied in the model predictive control algorithm is proposed, and the model predictive control algorithm is used to configure the flywheel energy storage device to achieve a smooth output power of the wind farm. Finally, the simulation is performed in MATLAB and the experimental parameters are adjusted. The experimental results show that the configuration of the flywheel energy storage system based on the model predictive control algorithm can effectively smooth the fluctuation of the high-frequency component of the output power data of the wind farm. The experimental results take the wind power data of different time periods for energy storage configuration, and the comparison verifies the reliability of the system designed in this paper.