Research On Active Power Coordinated Control Of Wind Power And Energy Storage Combined Generation Station

The utilization of large-scale renewable energy resources can effectively alleviate the shortage of traditional fossil fuel energy resources and the problem of environmental pollution.In order to realize the grid-friendly access of renewable energy power generation represented by wind power,it is necessary to involve energy storage,of which the battery energy storage is the most widely used type,and build a relatively controllable combined power generation system.The promotion of battery energy storage and renewable energy station as a consortium to participat e in grid operation optimization and to accept dispatching instruction can improve the renewable energy consumption and provide ancillary services for power grid.Under the background of universal existence of wind power curtailment phenomenon in large-scale wind power centralized area of China,this paper carries out the research on active power coordinated control of wind power and energy storage combined station.The main work and main results are as follows:Firstly,this paper analyzes the wind power characteristic from two aspects,fluctuation and variability.In the study of wind power fluctuation,the common methods for calculating wind power fluctuation are summarized,and the probability density distributions of wind power fluctuation at multiple minute time scales are obtained.The research shows that at minute time scales wind power presents the characteristics of small amplitude with large probability and large amplitude with small probability.In the study of variability of wind power,the probability density distribution of wind power prediction error is calculated by using non-parametric kernel density estimation method,and the confidence interval of wind power prediction power under given confidence is calculated based on this result,which provides a reference for considering wind power prediction error in the following study.In the study of power generation index tracking of wind power and energy storage combined station,two-stage active power control strategy considering both the tracking effect of power generation index and the safe operation of energy storage is proposed and an optimization model is established.In the day-ahead stage,according to the predicted wind power,the power generation index is initially allocated,and the tracking optimization model considering the prediction error of wind power interval is established.Then,the improved particle swarm optimization algorithm(PSO)is used to solve the model.In the real-time stage,on the basis of the previous optimization,the dynamic adjustment process of the real-time generation index is taken into account,and the active power of energy storage is revised by referring to the previous optimization results.The case study shows that energy storage can improve the tracking effect of power generation index,improve the utilization ratio of power generation index and reduce wind power curtailment.Compared with the traditional strategy of energy storage,the optimized strategy in this paper guarantees that the state of charge(SOC)of energy storage stays in proper interval at the cost of abandoning part of the wind power absorption space and deteriorating part of the tracking effect,which avoids the safety problems caused by energy storage.In the study of active power control of wind power and energy storage combined station offering frequency regulation ancillary service,the optimal model is established with the objective function of maximum revenue and minimum wind power curtailment.Considering the frequent changes of active power in response to frequency regulation instruction when the combined station participating in secondary frequency regulation ancillary service market,the cost of equivalent life loss of energy storage is taken into account in the optimization model.Considering the different dimension and magnitude of the two objective functions,the multi-objective particle swarm optimization algorithm(MOPSO)combined with technique for order preference by similarity to an ideal solution(TOPISIS)is used to solve the model.The case study shows that the optimization result helps to arrange active power of wind power and energy storage combined station and the capacity of energy storage to participate in the secondary frequency regulation ancillary service market on the next day.