Based on the coordinated optimization of transient control parameters for wind
solar
hydro
thermal
and energy storage
this paper optimizes the energy storage configuration in a new energy base. Firstly
by analyzing the transfer functions of wind
solar
hydro
thermal
and energy storage in the new energy base
the transient control parameters of each device are determined
and a comprehensive source-storage control model for the new energy base is established. Then
based on a convolutional neural network
three convolutional layers with different kernel sizes are set up and combined with a long short-term memory network to build a hybrid neural network model. This model is used to coordinate and optimize the transient control parameters of wind
solar
hydro
thermal
and energy storage
proposing a control strategy for the new energy base. Finally
based on the power deficit
a two-level optimization objective function for energy storage is established. By comparing the economic performance and transient stability enhancement capability of energy storage under different scenarios
an optimized energy storage configuration method for the new energy base is proposed