首页> 外文会议>IEEE Conference on Industrial Electronics and Applications; 20070523-25; Harbin(CN) >Parameter Identification of Synchronous Generator by Using Ant Colony Optimization Algorithm
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Parameter Identification of Synchronous Generator by Using Ant Colony Optimization Algorithm

机译:蚁群算法在同步发电机参数辨识中的应用

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摘要

Aiming at the problems of parameter identification of synchronous generator, which needs long time and is easy to get into the local optimization, ant colony optimization (ACO) for parameter identification of synchronous generator in continuous space is proposed. When the problem is defined using ACO algorithm, it combines the advantage of rapidness and global optimization. Simulation results show that it is very effective. An experiment is carried out by the simulative generator whose type is MF-15. A step is added to the field system. And based on the transient behavior of the machine, the electrical parameters are identified by using the method proposed in the paper. Experimental results show that ACO is fit for continuous optimization of synchronous generator, and the method is valid and feasible.
机译:针对同步发电机参数辨识的问题,该问题需要较长的时间,并且容易进入局部优化,提出了一种连续空间同步发电机参数辨识的蚁群算法。当使用ACO算法定义问题时,它结合了快速和全局优化的优点。仿真结果表明该方法非常有效。由类型为MF-15的模拟生成器进行了实验。步骤已添加到现场系统。然后根据电机的瞬态特性,采用本文提出的方法识别电气参数。实验结果表明,ACO适用于同步发电机的连续优化,该方法是有效可行的。

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