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A Multiple-Model Approach for Synchronous Generator Nonlinear System Identification

机译:同步发电机非线性系统辨识的多模型方法

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A Multiple-Model Approach for Synchronous Generator Nonlinear System Identification In this paper, a multiple model approach is proposed for the identification of synchronous generators. In the literature, the same structure often is used for all local models. Therefore, to obtain a precise model for the operating condition of the synchronous generator with severely nonlinear behavior, many local models are required. The proposed method determines the complexity of local models based on complexity of behavior of the synchronous generator at different operating conditions. There are two choices for increasing model precision at each iteration of the proposed method: (i) increasing the number of local models in one region, or (ii) increasing local model complexity in the same region. The proposed method has been tested on experimental data collected on a 3 kVA micro-machine. In the study, the field voltage is considered as the input and the active output power and the terminal voltage are considered as the outputs of the synchronous generator. The proposed method provides a more precise model with fewer parameters compared to some well known methods such as LOLIMOT and global polynomial models.
机译:用于同步发电机非线性系统辨识的多模型方法本文提出了一种用于同步发电机辨识的多模型方法。在文献中,所有本地模型通常使用相同的结构。因此,为了获得具有严重非线性行为的同步发电机工作状态的精确模型,需要许多局部模型。所提出的方法基于同步发电机在不同工况下的行为复杂度来确定局部模型的复杂度。在所提出方法的每次迭代中,有两种选择可提高模型精度:(i)增加一个区域中局部模型的数量,或(ii)增加同一区域中局部模型的复杂性。所提出的方法已在3 kVA微型计算机上收集的实验数据上进行了测试。在研究中,励磁电压被视为同步发电机的输入,有功输出功率和端电压被视为同步发电机的输出。与某些众所周知的方法(例如LOLIMOT和全局多项式模型)相比,所提出的方法使用较少的参数提供了更精确的模型。

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