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A Method for Online Identification of a Subset of Synchronous Generator Fundamental Parameters from Monitoring Systems Data

机译:一种用于在监控系统数据中在线识别同步发电机基本参数的子集

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Monitoring systems are common in small and large power plants, providing measurements of basic electrical, mechanical and thermal variables. These measurements can be used for the identification of the synchronous generator parameters. In this paper, a simple method for the identification of a subset of synchronous generator parameters, using basic measurements provided by monitoring systems, is proposed. The identification is performed in normal operating conditions using a synchronous machine simplified model suited for operating conditions under small disturbances. Three identification models are derived, each one depending on a subset of parameters. Three optimization subproblems are then solved by minimizing the residues between each model output and a system measurement. The resulting nonlinear least squares problems are solved by the interior-point method taking into account constraints on the parameters range. A method is proposed to estimate the load angle which is required in the identification. Results are presented for synthetic data and real data, from a 25 MVA generator in a hydroelectric power plant.
机译:监控系统在小型和大型发电厂中很常见,提供基本电气,机械和热变量的测量。这些测量可用于识别同步发电机参数。在本文中,提出了一种简单的方法,用于识别同步发电机参数的子集,使用监控系统提供的基本测量。使用适合于在小扰动下操作条件的同步机简化模型在正常操作条件下进行识别。派生三种识别模型,每个识别模型取决于参数的子集。然后通过最小化每个模型输出和系统测量之间的残留物来解决三个优化子问题。由此产生的非线性最小二乘问题通过在参数范围内考虑到限制的内部点方法来解决。提出了一种方法来估计识别中所需的负载角。结果为合成数据和实际数据,来自水力发电设备中的25个MVA发生器。

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