Maximum Power Tracking for Low Frequency Offshore Wind Farm Based on Wind Speed Prediction by Convolutional Neural Network Algorithm

The wind turbines in low-frequency offshore wind farms can achieve the goal of efficient utilization of wind energy by adjusting the low-frequency side frequency to change the operating status of the wind turbines. This article establishes a power-frequency model for wind farms by analyzing the operating characteristics of low-frequency wind farm. The frequency optimization algorithm is used to obtain the optimal operating frequency of the wind farm and achieve maximum power tracking of the wind farm. Convolutional neural network(CNN) is used for ultra-short-term prediction of offshore wind speed, thus a wind speed model is established for low-frequency wind farm. Then, through the analysis and verification of examples, the low-frequency wind farm can track the change of wind speed in real time to adjust the operating frequency, and then to realize the maximum power tracking of the wind farm.