一种基于凸化预测模型的风力发电机组控制方法
By performing mechanistic modeling and convex predictive model control on wind turbine generator sets, the problem of high solution complexity in wind turbine generator set control was solved, and the power of wind turbine generator sets was maximized and fatigue load was minimized, thereby improving the system's working efficiency and control accuracy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NORTH CHINA ELECTRIC POWER UNIV
- Filing Date
- 2023-12-27
- Publication Date
- 2026-07-17
AI Technical Summary
Existing wind turbine control methods suffer from high solution complexity and low turbine operating efficiency. In particular, they are prone to getting trapped in local optima in non-convex optimal control problems, leading to feedback delays and power losses.
A control method based on a convex prediction model is adopted. By performing mechanistic modeling of the wind turbine generator, reconstructing the decision variables, transforming it into a linear dynamic system, and making the constraint set convex, a convex prediction model control strategy is designed to solve the optimization problem and determine the optimal control variables for generator torque and pitch angle.
This approach maximizes the power output of wind turbine generators and minimizes fatigue load, reducing system computational complexity and improving control precision and operational efficiency.
Smart Images
Figure CN117869178B_ABST