Self-adaptation excitation control method for synchronous generator

A synchronous generator and excitation control technology, which is applied in the fields of controlling generators through magnetic field changes, electrical digital data processing, special data processing applications, etc., can solve the problems of synchronous generator excitation multi-parameter setting coupling difficulties, poor adaptive control and other problems , to achieve the effect of reliable operation, accelerated calculation and analysis

Inactive Publication Date: 2013-09-18
NANCHANG HANGKONG UNIVERSITY
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Problems solved by technology

[0003] The purpose of the present invention is to provide a synchronous generator adaptive excitation control method, which over

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  • Self-adaptation excitation control method for synchronous generator
  • Self-adaptation excitation control method for synchronous generator
  • Self-adaptation excitation control method for synchronous generator

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Example Embodiment

[0024] Embodiments of the present invention are described in detail below in conjunction with accompanying drawings:

[0025] figure 1 It is a CMAC and PID composite control system diagram based on one-dimensional multi-agent genetic algorithm optimization. PID controller and synchronous generator constitute feedback control, CMAC realizes feedforward control, and CMAC input V ref and e=V ref -V t , respectively represent the generator terminal voltage expected output and the system tracking voltage error.

[0026] The working process of the coordinated and optimized PID and CMAC intelligent synchronous generator excitation controller is divided into two stages: control and learning. At the beginning of control, the weight of CMAC is initialized to 0, and the learning rate and inertia can be initialized to a very small number; the three control parameters of the PID controller only need to be within the range of its stable domain, according to the traditional PID parameter ...

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Abstract

A self-adaptation excitation control method for a synchronous generator is characterized by including: preliminarily determining a stability domain of each control parameter according to the principle of satiability; combining MAGA (multi-agent genetic algorithm), CMAC (cerebellar model articulation controller) and a PID (proportional-integral-derivative) controller, and using global optimization capability of MAGA for optimization in determined stability domains of control parameters Kp, Ki, Kd, eta and alpha; obtaining the optimal control parameter combination according to certain control objective function minimum principles so as to realize synchronous generator self-adaptation excitation control. By using distributed control of a one-dimensional multi-agent control system, the control parameters can be harmonized and optimized, the problem that intelligent multi-parameter coupling and multiple control parameters are difficult to determine is solved, synchronous generator self-adaptation excitation control is achieved, operation and analysis of a control system are accelerated, and the synchronous generator can be operated economically while safe, stable, economical and reliable operation of a power grid is guaranteed.

Description

technical field [0001] The invention relates to an excitation control method of a synchronous generator. Background technique [0002] The synchronous generator excitation control system is a complex control system with strong nonlinearity. Therefore, the system has the characteristics of high uncertainty, nonlinearity, time-varying parameters, and strong coupling. With the interconnection of large-capacity units and large-scale power systems, the The control quality of the synchronous generator system puts forward higher requirements, and the conventional PID control is difficult to achieve the ideal control effect. Seeking a control method with strong adaptability, robustness and good real-time performance is an urgent problem to be solved in excitation control of synchronous generators. The cerebellum model neural network (CMAC) has the advantages of dealing with nonlinearity, self-learning, and certain generalization capabilities. The composite control composed of CMAC...

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Application Information

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IPC IPC(8): H02P9/14G06F19/00
Inventor 程若发江晓舟
Owner NANCHANG HANGKONG UNIVERSITY
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