Fractional-order control method for doubly-fed induction generator grid connection process

Abstract

The invention discloses a fractional-order control method for a doubly-fed induction generator grid connection process, and the method comprises the following steps: constructing a motor control modeland a fractional-order operator; for a doubly-fed wind power generation system, using a continuous transfer function method to rationalize the fractional-order operator, i.e., using a rational transfer function is to effectively simulate the fractional-order operator in amplitude-frequency characteristics and phase-frequency characteristics; and establishing a fractional-order PI [lambda] controller to control a motor control model and to control a doubly-fed induction generator no-load grid connection process. The fractional-order PI[lambda] controller can effectively reduce the active powerand reactive power of a starting phase, so that the system enters the steady-state stage smoothly, avoiding the excessive impact on the power grid; The fractional-order PI[lambda] control method canalso be used to reduce the system oscillation under a short-circuit fault condition.

Description

technical field [0001] The invention relates to the technical field of control, in particular to a fractional-order control method for a doubly-fed induction generator grid-connected process. Background technique [0002] Doubly-fed induction generator (DFIG) is widely used in variable-speed constant-frequency wind power generation systems because of its flexible frequency control, good regulation performance, good dynamic and steady-state characteristics, and decoupling control of active and reactive power. and ship power systems. The control of the doubly-fed induction generator is realized through the control of the rotor AC excitation converter. The stator and rotor system of the doubly-fed induction motor is a strongly coupled system. In order to achieve decoupling control, the vector control method of stator flux orientation is often used to decompose the AC into active power and reactive power, and a double closed-loop PI regulator is used to separate Take control o...

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Problems solved by technology

[0005] 1. Use the RBF neural network to adjust the parameters of the PID controller online to deal with the influence of system parameter uncertainty and external disturbance on the control performance, but it requires more historical data and the training process is longer

[0006] 2. A neural network-based integral sliding mode control strategy is proposed. It is verified that the method has strong robustness to disturbances and has good grid-connected performance. However, the chattering phenomenon of the sliding mode control strategy is not can solve

[0007] 3. Propose

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