Prediction and tracking control method of wind driven generator at low wind speed

Abstract

The invention discloses a prediction and tracking control method of a wind driven generator at low wind speed. The method comprises the following steps: 1) the optimal angular speed of a wind wheel of the wind driven generator is predicted; and 2) a controller is designed to perform tracking control on the angular speed of the wind wheel of the wind driven generator. The prediction and tracking control method of the wind driven generator at low wind speed can accurately predict the wind speed of entering a wind field in a period of time in the future to obtain ideal predicting angular speed data near the real angular speed of the wind wheel of the wind driven generator at the future time, can prevent the problem of late control through accurately controlling the angular speed of the wind wheel of the wind driven generator and tracking the ideal predicting angular speed, increases the wind energy utilization rate of the wind driven generator, and enables the wind driven generator to output by the maximum power at low wind speed; and a designed RBF neural network self-adaption controller only depends on the system angular speed errors, and also can control the rotating speed of the wind driven generator under the condition of not knowing part of functions and parameters in a system.

Description

technical field [0001] The invention relates to the technical field of wind power generation operation control, in particular to a prediction and tracking control method for wind power generators at low wind speeds. Background technique [0002] 1) At present, there is a shortage of non-renewable energy such as coal, charcoal, and petroleum in the world. New energy such as wind energy and solar energy are renewable resources, which are inexhaustible, widely distributed, clean and pollution-free, and have been obtained in recent years. attention and research from all over the world. Our country has a vast territory and abundant wind energy resources, so wind power generation has been vigorously developed in our country. [0003] 2) At present, there are some defects in the tracking control of wind power generator output power in wind power generation. For example, when the wind enters the wind farm, the fan blades of the wind turbine are driven to rotate to generate electri...

AI Technical Summary

Problems solved by technology

For example, when the wind enters the wind farm, the fan blades of the wind turbine are driven to rotate to generate electricity. There are certain deficiencies in the method of using the wind speed, rotation speed and other data measured by the internal sensor of the wind turbine to control the wind turbine. Due to the large inertia of the wind turbine, in There will be a time delay in the control, resulting in the problem that the control is not timely; another example is that the current wind turbine mainly uses the PID control method, which has the disadvantages of long tracking time, prone to oscillation, weak stability, etc.

Untimely control or low controller efficiency will directly affect the utilization rate of wind energy resources by wind turbines, resulting in waste of wind resources, especially when the wind speed is lower than the rated wind speed of the wind turbine and the power generation is low

[0004] 3) The invention patent with the publication number CNIO556992OA discloses "a control method and control system for wind power generators". The invention obtains the current wind speed and pitch angle, uses the current wind speed to calculate the ideal pitch angle, and controls the pitch angle Angle tracking ideal angle, this method uses real-time wind speed, there is a problem of untimely control

[0005] 4) The invention patent with the publication number CNIO4963811A discloses a "multi-stage wind-driven generator with adaptive wind speed and its control method". The problem of untimely control

This method is not accurate enough for the establishment of the model and can only be used for qualitative analysis, which is not suitable for engineering practice.

[0007] 6) The invention patent with the publication number CNIO4612898A discloses "a wind power variable pitch multivariable fuzzy neural network PID control method". This invention mainly uses the control method of fuzzy neural network PID. Good, high reliability, but it is difficult to meet the control requirements for wind speed in complex situations, and it is easy to cause vibration or untimely control

[0008] 7) The invention patent with the publication number CNIO4408223A discloses "a tracking optimization control method for wind turbines". This invention uses a robust adaptive control method to control the electromagnetic torque of the wind turbine. The advantage of this method is that it can To a certain extent, the control of wind turbines can better track the ideal curve, but one disadvantage is that no equipment such as wind measuring towers are added, and there is no way to describe the ideal curve acquisition method.

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