Modeling And Intelligent Control For Wind Permanent Synchronous Generator Systems

The research of new energy and renewable resources has become more and more important as the development of energy and environment problems.Wind turbine has been developing rapidly in recent years,which is used as a kind of wind power plant.The permanent magnet synchronous generator(PMSG)has been widely used because of its easiness to control and the simple structure.In this paper,studies were made on how to build the system model and control the PMSG intelligently.A system modeling and simulation in Simulink was set up based on fundamentals and relative knowledge of the PMSG.A PID controller was proposed on BP neural network rather than traditional PI control due to the latter's defect,and the intelligent control was studied with the wind power system model.Meanwhile,the related output control was studied on the maximum power output of the wind turbine under the rated wind speed.At the same time,a new BP neural network module was established using the wavelet function to forecast the wind speed.As poor initial values decreased the performance of the BP module,this problem was solved by the application of genetic algorithm(GA).This method was proved feasible in improving the performance of the BP module by simulation.First of all,the relevant aerodynamic and the control technology was introduced about wind turbine in this paper,with the discussion about its mechanical model and operating principle.The basic wind turbine model was established according to the theory of aerodynamic,which was decoupled by Clark and Park transformation.Moreover,a wind turbine simulation model was proposed under the synchronization reference frame.Secondly,the basic structure was presented of the Direct-driven PMSG current system,followed by discussions on several common algorithms and working principles of the three-phase voltage source PWM inverter with a focus of the implementation and modeling of SVPWM algorithm.Studies were also carried out on the principle and implementation of vector control technology of three-phase PMSG.A simulation model was built on the current loop and the speed loop by means of optimal PI controller parameter design.Eventually,a mathematical model was achieved based on Simulink for the three-phase permanent magnet synchronous generator.Thirdly,several control strategies were introduced on the outgoing control of maximum power point tracking(MPPT)to solve the problem of insufficient utilization rates of the wind turbine under rated wind speeds.Considering both the control effectiveness and feasibility,the optimum tip-speed ratio control was selected to realized the maximum output of PMSG power system afterwards.Fourthly,studies were made on the popular neural network intelligent algorithms with an emphasis of the BP neural network.And a BP neural network smart control model was proposed on BP neural network control technology.Besides,an optimized model was established to improve the performance stability of the BP neural network controller.Finally,the BP neural network module was set up on wavelet function,which was used for wind speed forecasting with weather conditions and history data of wind speeds imported.At the same time,a new wavelet-BP module was built based on GA to solve the susceptibility of the network performance to initial parameters.This module was proved effective at improving network performance and the forecast precision.Then the wind turbine power control model was built based on wind forecast,it can keep wind turbine run stably and efficiently.This paper provides some solutions and references about intelligent control for nonlinear control problems.