Joint Control Strategy of Wind Storage System Based on Temporal Pattern Attention and Bidirectional Gated Recurrent Unit

Increasing wind power penetration will profoundly impact a power system’s operating mechanism. It is necessary to study a control strategy so that wind farms can use energy storage to improve their controllability to the level of traditional units. Therefore, this paper proposes a control strategy for wind storage systems based on temporal pattern attention (TPA) and bidirectional gated recurrent units (BiGRUs). The control strategy uses BiGRU to extract the time series information between the energy storage output, the actual output of the wind farm, and the energy storage state, which improves the control stability of a wind storage system. At the same time, TPA is introduced to assign different weights to the hidden layer state of the neural network to highlight the importance of local time series information to the current energy storage output, effectively improving the model performance and reducing the control deviation. Finally, the stability and superiority of the proposed control strategy are verified based on an actual wind farm dataset. The economy of the wind storage system with this control strategy improves significantly.