Smart Operation Control Of Wind Farm Based On Stochastic Model Predictive Algorithm

The characteristics of wind power randomness and volatility,the high order,nonlinear and strong coupling of wind turbine system make how to control the active power output of wind turbine better and actively cooperate with the dispatching requirements of power grid become a hot research topic.The performance of the system with strong random disturbance in the predictive control algorithm of stochastic model is better,which opens up a new way for the wind power system.In this paper,the stochastic model predictive control strategy is applied to the wind power generation system.By effectively reducing the influence of random disturbance of wind speed,the stability of active power output of wind turbine and the accuracy of scheduling signal tracking are improved.This control strategy is combined with load response scheduling to improve the scheduling economic benefits of the wind power system,So as to realize the intelligent operation control of wind farm.The main research contents are as follows:(1)Taking the doubly-fed asynchronous wind generator as the research object,the principle of wind energy conversion is introduced in detail,and the combined wind speed model,wind turbine,transmission system,shaft model and generator model are established,and the working principle of each component is analyzed in turn.Based on the random characteristics and utilization principles of wind energy,combined with the models built by each part of the wind turbine,comprehensively considering multiple influencing factors of the wind power system,a nonlinear model of the wind power system is finally established.(2)Combining the random wind speed and the nonlinear characteristics of the generator set,the wind turbine torque equation is applied with a small disturbance at the nominal operating point,so as to carry out the first-order Taylor expansion,and the nonlinear model of the generator output is also linearized.Then the linearized model is discretized by the fourth-order Runge-Kutta method,wind speed is used as a random disturbance input,combined with the constraints of the state variables,input and output variables in the actual operation of the wind turbine,the corresponding target is given Function,a stochastic model of wind power generation system considering wind speed disturbance is established.(3)In the active power control layer of the wind farm,the stochastic model predictive control method is used to design the master controller at the station level,which takes into account the various constraints that should be met when the wind turbine operates safely and normally,as well as the power changes when the wind farm is connected to the grid.In the discrete time interval [0,300],the tracking and control effects of stochastic model predictive control and PI control on the active power output of wind farm are compared.The results of SMPC control on the active power output of wind turbine show that: under the interference of random wind speed,the error between the predicted value at the next moment and the output value at the current moment is used as the feedback correction value,which is substituted into the next operation.This is more effective for the stability of active power and more accurate for the tracking of dispatching signal.(4)Aiming at the huge challenges brought by the continuous and rapid increase in the scale of wind power grid connection to the operation stability and dispatching economy of the power system,a joint load response dispatching model based on SMPC is proposed.Comparing the operating costs of the system with load response and no-load response,it can be seen that in the case of drastic wind speed fluctuations,flexible load resources are dispatched to absorb more wind energy,which increases the utilization rate of wind power,and the cost of wind power system operation and management the economic benefits of wind power companies are guaranteed.(5)Finally,this paper combines the stochastic model predictive control algorithm with the nonlinear model of wind power generation system.The rolling optimization and feedback correction characteristics of the algorithm provide a solution for the active power tracking of wind power system and the participation of wind farms in power system scheduling.At the same time,the shortcomings of the existing research are prospected.The next research direction and focus is to establish a more realistic wind speed model,consider the multi degree of freedom wind turbine model and reactive power control of wind farm.