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A Quantum Migration Parallel Multilayer Monte Carlo Parameter Optimization Method for Doubly-fed Fans

An optimization method, double-fed fan technology, applied in complex mathematical operations, computer components, instruments, etc., can solve difficult problems

Active Publication Date: 2022-06-21
GUANGXI UNIV
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Problems solved by technology

Therefore, it is very difficult to optimize the parameters of the rotor-side controller and obtain satisfactory control performance by using the traditional engineering tuning method and the classical self-tuning method

Method used

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  • A Quantum Migration Parallel Multilayer Monte Carlo Parameter Optimization Method for Doubly-fed Fans
  • A Quantum Migration Parallel Multilayer Monte Carlo Parameter Optimization Method for Doubly-fed Fans
  • A Quantum Migration Parallel Multilayer Monte Carlo Parameter Optimization Method for Doubly-fed Fans

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Embodiment Construction

[0047] A method for parameter optimization of a quantum migration parallel multi-layer Monte Carlo doubly-fed fan proposed by the present invention is described in detail as follows with reference to the accompanying drawings:

[0048] figure 1 It is the frame diagram of the proportional integral derivative parameter optimization of the rotor side controller of the doubly-fed fan according to the method of the present invention. The design of the rotor-side controller of the doubly-fed induction generator is based on the vector control under the orientation of the stator flux linkage combined with the traditional proportional-integral-derivative control. The proportional integral derivative controller has the characteristics of reliable operation, simple structure, easy adjustment, and easy realization with general electronic circuits and motor equipment. It is the main control method in engineering practice.

[0049] The purpose of adopting the vector control strategy of sta...

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Abstract

The invention proposes a parameter optimization method of quantum migration parallel multi-layer Monte Carlo double-fed fan, which includes a population encoding method based on the probability amplitude of qubits and a migration parallel multi-layer Monte Carlo method optimization method; at the same time, it proposes a double-fed fan rotor Optimization framework for proportional-integral-derivative parameters of side controllers. First, the population encoding method based on the probability amplitude of qubits generates Monte Carlo random points, which can improve the diversity of the population when the population number remains unchanged. Then, multiple sets of proportional-integral-differential parameters and fitness values ​​reflecting the performance of the controller are obtained through multi-layer and multi-granularity parallel multi-layer Monte Carlo method. Second, transfer learning is used to learn past experience and knowledge to improve the optimization calculation speed. Finally, the proportional-integral-derivative parameters of the double-fed fan rotor side controller with good control performance are obtained through the parallel multi-layer Monte Carlo optimization method with multiple layers and granularity.

Description

technical field [0001] The invention belongs to the field of wind power generation control, and relates to a controller parameter optimization method, which is suitable for parameter optimization of a rotor-side controller of a doubly-fed fan. Background technique [0002] In recent years, the application of DFIG in the field of wind power generation has become a research hotspot and has great development prospects and commercial value. The vector method combined with the proportional-integral-derivative control method is widely used in the wind power generation industry based on the doubly-fed wind turbine because of its easy-to-implement structure and decoupling control between the output powers. The DFIG system is a high-order, nonlinear, strongly coupled, and time-delayed system. Therefore, it is very difficult to optimize the parameters of the rotor-side controller and obtain satisfactory control performance by using the traditional engineering tuning method and the cl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/18G06N3/00G06K9/62
CPCG06N3/006G06F17/18G06F18/214
Inventor 殷林飞黄天蔚马晨骁高放
Owner GUANGXI UNIV