Research On Capacity Configuration Method And Control Strategy Of Battery Energy Storages Participating In Power System Frequency Regulation

With the large-scale intergration of renewable energy such as wind power and photovoltaics,its weak inertia,volatility and uncertainy will bring challenges to the frequency regulation of power systems.Hydropower and thermal power units are limited by their own ramp rate,and their response speed is relatively slow,so it will be difficult to meet the frequency regulation requirements of the power grid in the future.It is necessary to introduce more high-quality frequency regulation resources into the power system.In recent years,energy storage,especially battery energy storage,has developed rapidly,its cost has been decreasing year by year,and it has some good characteristics such as fast response,flexible charging and discharging,and accurate tracking.It is regarded as one of the most promising frequency regulation sources.On the basis of reviewing the current research of grid frequency regulation and battery energy storage,this paper focuses on the capacity configuration method and control strategy of battery energy storage participating in grid frequency regulation.The main work of this paper is as follows:First,focus on the primary frequency regulation of power system,this paper proposes a multi-objective energy storage capacity configuration method to prevent transient low-frequency load shedding of the power grid.Based on the equivalent frequency response model of the power system,this paper proposes a multi-objective dynamic optimization model with piecewise function constraints which is suitable for energy storage capacity configuration,aiming to consider the two conflicting objectives of energy storage,the configuration cost and transient frequency regulation performance at the same time.The big M method and implicit trapezoid integration method are used to transform the multi-objective dynamic optimization model into a multi-objective mixed integer quadratic programming model.The normalized normal constraint method is used to obtain the Pareto optimal solution.The effectiveness of the proposed multi-objective energy storage capacity configuration model is validated with the simulation result based on IEEE 24 bus power system.Secondly,focus on the secondary frequency regulation of power system,this paper proposes a simulation based capacity configuration method for batteries energy storage which participating in fast frequency regulation.An equivalent frequency response model including a fast frequency regulation controller and an energy storage battery control model is established.The control performance index proposed by the North American Electric Power Reliability Commission is used as an index to evaluate the frequency regulation performance of the power grid under different energy storage configuration schemes.This method traverses different energy storage battery configuration combinations,and obtains the configuration decision diagram of the energy storage battery capacity according to the simulation results of each configuration scheme,so as to evaluate the economics of energy storage investment and the effect of frequency regulation.The effectiveness of the proposed energy storage capacity configuration method is validated with the simulation result based on IEEE 24 bus power system.Finally,based on the configuration of the energy storage battery which participating secondary frequency regulation,this paper studies the control strategy of the energy storage battery participating in the secondary frequency regulation of the power grid.Based on model predictive control,a control method considering degradation cost for the batteries energy storage participanting in the frequency regulation market is proposed,in order to balance the benefits of batteries energy storage with their own degradation costs.The future frequency regulation instructions are predicted by the time series analysis method.The piecewise linear cost function is used to model the battery cycle aging cost.The response of the battery is obtained by solving the model predictive control optimization problem.Real frequency regulation signals and batteries energy storage parameters are used for the simulation verification.The simulation results indicates that the use of the proposed method can reduce the energy storage degradation cost while maintaining a high frequency regulation performance score,which increases the total profits of the BES in the frequency regualtion market.