Grid-Connected Coordinated Control Of Wind Farm Cluster Based On Risk Elimination Constraints

Wind energy is a new energy with clean and renewable characteristics.The increasingly mature wind power technology has made many countries pay close attention to its development.Therefore,a large amount of wind power is injected into the power grid.With the large-scale access of wind power in the power system and the increasing popularity of wind power,it has a great impact on the power grid security and stability,the traditional method of proportional distribution cannot effectively solve these problems caused by largescale wind power integration,and a large-scale wind power grid-connected control method is needed to digest large scale wind power instead of abandoning it and to optimize the utilization of wind energy resources to enhance the accuracy of the cluster's active output and voltage stability.Therefore,research on the grid-connected control strategy of wind farm cluster is very necessary.Main tasks as follows:Through the study of the wake effect,two models are used to simulate the influence of the wake effect on the overall output of the wind farm,and consider the influence of the delay of the wind between the equivalent turbines,and finally in the case of the wake effect and the delay effect of the wind,establishing wind farm multi-machine equivalent model.Simulation on the simulation software verifies that the multi-equipment equivalent model is more in line with the actual output characteristics of the wind farm cluster than the single-machine equivalent model.Based on the stratification theory,a control strategy for reducing the grid-connected error of active power is designed to optimize the active power of the wind farm cluster.This method takes the grid-connected condition as a constraint,minimizes the error as the target,and optimizes the rational allocation of the active power between the wind farms.The strategy of control enables the active output of the cluster to track the reference value more accurately.Finally,the control effect of the strategy is verified by simulation.The neural network algorithm is combined with the model predictive control,and the method is applied to the real-time rolling optimization control of the wind farm.Finally,the simulation proves that the method can effectively reduce the error and achieve precise control of the active power output of the wind farm.A control strategy to reduce voltage fluctuation is designed to optimize the reactive voltage of the wind farm cluster.The cluster layer adopts two control models: optimization and coordination.The wind farm uses neural network model predictive control.The strategy considers the complementarity among the wind farm and the coordination between the collection substation and wind farm,and the simulation analysis is carried out.The results show that this strategy can effectively reduce voltage fluctuations and reduce the impact of voltage fluctuations on the grid.