Study On Nonlinear Dynamic Behavior And Synchronous Control Of Complex Power Systems

The power system can be regarded as a large-scale complex network composed of power generation equipment,substation and high-voltage transmission line as the nodes and connections of the network.It is a multi-variable,strong-coupling and strong nonlinear system.In recent years,with the development of science and technology,the green renewable energy represented by distributed wind power generation has gradually attracted the attention of governments of all countries,thus the interconnection between wind generator network and power grid has become the inevitable trend of power system development.Moreover,with the increasing number of users of power consumption,the number of loads of the power system is gradually increasing,which brings great challenges to its stable operation.Studies have shown that power system will generate chaotic oscillations phenomenon under the condition of certain parameters and working,chaotic oscillation is one of the important factors that cause the instability of the wind turbine network when it is connected to the power grid and the power grid with the load network interconnection.Therefore,it is especially important to study the nonlinear dynamic behavior of power systems and its synchronous control to maintain the stable operation of the power system.This paper is mainly divided into two aspects: first,the chaos synchronization control between the wind generator network and the power grid is studied by using the Kuramoto-like model as the power grid model and the permanent magnet synchronous wind generator(PMSG)as the node of the wind generator network.Secondly,the chaotic oscillation synchronization control between the wind turbine network and the load network is studied by using the permanent magnet synchronous motor(PMSM)as the node of the load network.The detailed work arrangement of the paper is as follows:(1)Introduce the typical mathematical model of power grid,permanent magnet synchronous wind turbine and permanent magnet synchronous motor,and draw the phase diagram of the chaotic behavior of PMSG and PMSM single system under certain parameters,and then the wind turbine network model and the inductive load network model are constructed by using PMSG and PMSM as nodes respectively,and the nonlinear behavior of the network is analyzed.(2)Based on Lyapunov stability theory and finite-time stability theory,a nonlinear controller is improved.The problem of chaotic oscillation synchronization control between WS-based small world wind turbine network and power grid is studied.It is found that the improved nonlinear controller can achieve chaotic synchronization control between the wind turbine network and the power grid,and the synchronization time can be changed by adjusting the parameter values of the controller,solved the problem that the controller control time is long in the past.The controller not only has better control effect,but also has a simple structure and is easy to implement.(3)Based on the Lyapunov stability theory,the chaotic synchronization control between the interacting wind turbine network and the inductive load network is studied.Firstly,PMSG and PMSM are used as nodes of two networks respectively.An adaptive method is designed for the interacting PMSG and PMSM networks.The controller realizes chaotic synchronization control of the PMSG and the PMSM network.The controller is not only simple in structure,but also has low control cost and high control efficiency.(4)Using PMSG network as the driving system and PMSM network as the response system,based on Lyapunov stability theory and projection synchronization method,a nonlinear chaotic controller is designed and applied to the response system,chaos synchronization control between the WS-based small world wind turbine network and the inductive load network is studied.The research shows that the controller can realize the chaotic synchronization control between the wind turbine network and the inductive load network,and has the advantages of fast control speed,remarkable control effect and low control cost.