A Layered Scheduling Strategy for Wind Power Cluster Considering Entropy Variable Weight Evaluation

The paper proposes a hierarchical optimization control concept for wind power cluster control, which divided the wind power cluster into cluster layer, group layer, and wind farm layer. The wind farms within the cluster were grouped based on their ramping rates, and then the wind farms within each group were sorted based on their load rates. The power grid command was first issued from the cluster layer to the group layer, and then to the wind farms within the group, with scheduling carried out sequentially in a layered manner. Firstly, constructed a scheduling process based on control objectives and constraints. Then, through simulation of a large-scale base example and comparison with the traditional proportional allocation method, verified the feasibility and effectiveness of the proposed cluster allocation strategy in reducing the regulation frequency and volatility of wind farms in terms of power grid command tracking and scheduling sequence. Lastly, evaluated the performance of power reduction for each wind farm using the entropy method and variable weight theory, and the results demonstrate that the proposed strategy effectively improve the cluster volatility.