State Estimation Of Active Distribution System With Battery Energy Storage

With the grid connected operation of distributed power sources such as wind power generation and photovoltaic power generation,the distribution system has gradually changed from the traditional "network load" binary structure to the "source network load" ternary structure,and the traditional distribution system has evolved into an active distribution system.A large number of distributed energy access makes the system have better initiative and improves the regulation ability of active distribution system.However,for the power grid,a large number of distributed energy access,so that the entire distribution system contains random and fluctuating power supply,will aggravate the frequent fluctuation of grid voltage,impact on the grid,resulting in poor power quality,grid operation stability and other problems.The comprehensive perception of "source network load" is the basis of active control,active management and active service of active distribution system.State estimation is the basic tool of situation awareness in active distribution system,which is of great significance to the safe and stable operation of active distribution system.However,the traditional state estimation of power system is to estimate the operation state of the system under the steady-state condition,which belongs to the static estimation.It is no longer applicable in the active distribution system with dynamic distributed power.It is urgent to find a state estimation method suitable for the joint estimation of dynamic system and static system to sense the whole active distribution system.Therefore,this thesis proposes a state estimation of active distribution system with battery energy storage system,and studies the battery energy storage system model,system state estimation method and grid connection estimation model of battery energy storage system,aiming to bridge the gap between the joint state estimation of dynamic system and static system.In this thesis,firstly,the most widely used battery energy storage system ismodeled,and the rationality of the battery energy storage system model is verified based on the parameter identification of the model.Secondly,based on the equivalence between the iterative extended Kalman filter correction stage and the weighted least squares regression,a state estimation method is proposed to jointly estimate the static and dynamic variables of the distribution system,including the state of Charge,SOC),and then set up the energy storage system grid connection equivalent model with the battery as the energy storage unit,deduced the state transfer equation and the measurement equation of the battery energy storage system,combined the measurement equation of the distribution system to carry out the joint state estimation,and proposed a method of bad data detection,identification and correction applied to the active distribution system.Finally,the IEEE 33 node distribution system is selected,and the battery energy storage model is connected in the node to estimate the active distribution system with the grid connected structure of the battery energy storage system.From the simulation results of the model built in this thesis,it can be seen that the joint estimation framework contains the overall state estimation accuracy of the active distribution system with the grid connected structure of the battery energy storage system,and has a good ability of bad data detection and processing,which provides a comprehensive situation awareness for the whole system and lays a foundation for the large-scale grid connected and stable operation of the distributed energy in the later stage.