Based On Model Predictive Control Algorithm For Active Control Of Wind Farms

The wind power have special feature of random and intermittent. The wind turbine generator have inherent characteristics of nonlinear, tight coupling and uncertainty about active power output, especially, in the wind velocity changed environment. The all o f that will make people in trouble of wind power control and the plan of electric power dispatching. In order to solve these problems, the wind turbine need to have ability to regulate and control, assure the active power output of wind power plant not exceed the reference value of given. Model predictive control can implement coordinated and control wind power output in the condition of uncertainty wind speed, In order to satisfy the demands of track scheduling with constraint conditions.The article research the control principle and algorithm of model predictive control, and apply to wind power active power control system. This dissertation performed the following work based on the research before:1. Wind power active control system are analyzed, and its main components as well as the control target. Wind power active power control use the hierarchical control structure, field level centralized control and wind turbines control layer. In view of the control objectives, design level field concentrated model predictive control of the host controller in the control layer and distribution strategy in the assigned algorithm, realize the control of active power of wind farms, meet the scheduling requirements.2. Research on control principle and control algorithm of model predictive control, description model predictive control is applied to control system relative to the traditional control method. According to the principle of model predictive control algorithm is put forward need to modeling of wind farms, the wind farm as a whole without considering wind fan of specific distribution in its equivalent model is established, and a single unit of model is the basis of the wind farm equivalent model is set up.3. Due to field level centralized control allocation algorithm of layer distribution module will wind power allocated to each unit, the distribution of power as the power reference value of wind turbine control layer. The wind generator will be classified according to the running state, the combination of wind power generation capacity and scheduling, the relationship between the reference value of wind power prediction method are used to get the prediction power allocation algorithm is designed.4. Main controller is designed for field level centralized control layer. Establish the dynamic model of the wind farm to farm error between actual output power and the scheduling reference value as small as possible to the principle of design the control objective function of the model predictive control algorithm based on the wind farm grid in power rate requirements plus the fan itself capacity constraint conditions are obtained.In the last part, Combination wind speed model are adopted to simulate the wind farm in the wind speed data, and the scheduling of 20 of typhoon wind farm value simulation. We can contrast PI control and model predictive control in the same environment through the simulation, the results show that model predictive control is more efficient to control the wind farm active power output tracking scheduling reference signal under the wind speed disturbance.