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Nerve self-adaptation tracking control method for power of fans in wind field based on disturbance observer

A technology of adaptive tracking and disturbance observer, which is applied in the direction of adaptive control, general control system, control/regulation system, etc. It can solve the problems that need to be improved and do not take into account the mutual disturbance of wind turbines, etc.

Active Publication Date: 2018-10-30
青岛格莱瑞智能控制技术有限公司
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  • Abstract
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  • Application Information

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Problems solved by technology

However, in the existing control method, the mutual disturbance between the fans is not considered, so the effect of the output power of the control system to track the maximum power needs to be improved

Method used

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  • Nerve self-adaptation tracking control method for power of fans in wind field based on disturbance observer
  • Nerve self-adaptation tracking control method for power of fans in wind field based on disturbance observer
  • Nerve self-adaptation tracking control method for power of fans in wind field based on disturbance observer

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Embodiment Construction

[0084] The present invention will be further described below in conjunction with embodiment.

[0085] In this embodiment, the neural adaptive tracking control method based on the disturbance observer for the fan power of the wind farm includes the following steps:

[0086] Step 1: Establish a system model of fan power

[0087] Aerodynamic power P generated by the fan a for:

[0088]

[0089] Where ρ is the density of the wind, v is the wind speed, R is the radius of the fan rotor, C P (λ, β) represents the power conversion efficiency of the fan; β is the pitch angle of the blade.

[0090] The tip speed ratio λ is determined by the following formula:

[0091]

[0092] where ω r is the angular velocity of the fan rotor, so P a Another expression is

[0093] P a = ω r T a

[0094] T a represents the aerodynamic moment;

[0095]

[0096]

[0097] There is the following mathematical relationship between the fan rotor and the generator

[0098]

[0099] ...

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Abstract

The invention discloses a nerve self-adaptation tracking control method for the power of fans in a wind field based on a disturbance observer. The method includes the steps that 1, a systematic modelof the power of the fans is established; 2, a controller ui for controlling the maximum tracking power of the output power of the fans is designed as in the specification, and the self-adaptation lawis shown in the specification; 3, a calculated instruction obtained through the controller ui is input into a fan system, and the maximum output power for tracking the fans of the output power of thefans is controlled. According to the nerve self-adaptation tracking control method for the power of the fans in the wind field based on the disturbance observer, the controller can make the output power of the system better track an ideal maximum-power signal when mutual disturbance exists in the wind field, and it is ensured that the tracking errors of the system are approximate to zero.

Description

technical field [0001] The invention relates to the technical field of fan control in a wind field, in particular to a method for controlling a fan to track the maximum output power. Background technique [0002] Now wind energy is widely used. In terms of fan power control, many such as sliding film, fuzzy, optimal, reverse thrust control, etc. are combined with it to achieve the effect of tracking the maximum power. The wind farm power system involves a large number of wind turbines, and the mutual disturbance between the wind turbines will have a significant impact on the control of the wind turbines in the wind farm, which will have a significant impact on the controller's ability to control the output power of each fan in the wind farm to track the optimal output power. However, in the existing control method, the mutual disturbance between the fans is not considered, so the effect of the output power of the control system to track the maximum power needs to be improved...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/041
Inventor 宋永端刘秀兰高瑞赖俊峰黄秀财
Owner 青岛格莱瑞智能控制技术有限公司
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