Maximum power tracing optimization control method of low-wind-speed area of wind generating set

Abstract

The invention provides a maximum power tracing optimization control method of a low-wind-speed area of a wind generating set. The maximum power tracing optimization control method of the low-wind-speed area of the wind generating set mainly comprises three steps of acquiring and filtering a wind speed signal, designing an improved controller, and optimizing controller parameters. A signal acquisition part adopts a pulse laser radar to measure wind speeds of a wind wheel at different heights and different positions, and adopts an adaptive kalman filter algorithm to filter the wind speed signal;an improved controller design part introduces a super-twisted high-order sliding mode algorithm on the basis of traditional optimum torque control, so that a rotary speed tracing performance is improved; and a controller parameter optimization part adopts an improved particle swarm optimization algorithm, so that the defects that a conventional particle swarm optimization algorithm is easy to cause premature convergence and an oscillation phenomenon produced near a globally optimal solution in the later period of the algorithm are overcome. According to the maximum power tracing optimizationcontrol method of the low-wind-speed area of the wind generating set provided by the invention, the real-time changed wind speed can be effectively measured, and the performance of wind wheel rotary speed tracing real-time wind speed can be improved, so that the wind energy utilization rate is improved, and the method has a certain practical value.

Description

technical field [0001] The invention relates to the field of control of wind power generators, in particular to a maximum power tracking control method of wind turbines based on a super twist optimization algorithm. Background technique [0002] As we all know, energy and environmental problems are becoming more and more prominent in today's society. Traditional fossil energy can no longer meet the requirements of sustainable development due to its shortcomings such as serious pollution and non-renewability. Therefore, the development and utilization of new energy is particularly important. Wind power has gradually become one of the most promising new energy technologies due to its high energy utilization rate and relatively mature technology. [0003] According to the wind speed, the operating area of ​​wind turbines is usually divided into four parts: the part where the wind speed is lower than the cut-in wind speed, the area where the wind speed is between the cut-in wind...

AI Technical Summary

Problems solved by technology

At the same time, due to the randomness and time-varying nature of turbulent wind, the wind speed is constantly changing on the entire swept surface of the wind rotor, and the mechanical instrument has a moment of inertia, which cannot ensure the real-time and accuracy of wind speed measurement. Difficult to ensure optimal

In addition, the harsh natural environment of the wind farm will shorten the service life of the sensor

Therefore, most of the existing studies estimate the wind speed based on the output characteristics of the wind turbine, which has high estimation accuracy. Real-time control of fans, resulting in greatly reduced control performa

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