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Simultaneous Parameter Identification of Synchronous Generator and Excitation System Using Online Measurements

机译:在线测量的同步发电机与励磁系统参数同时辨识

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In this paper, a new method is presented to simultaneously identify parameters of synchronous generator and its excitation system (EXS) using measurement data. These measurements could be provided by metering devices such as data acquisition system or fault recorders of the power plant. Since a smart grid is capable of providing synchronized measurements using phasor measurement units, the desired data could also be provided by these devices. In the proposed method, the reference voltage of the EXS is considered as the input signal, while the terminal voltage and output active power of the machine are considered as output signals. The desired parameters are classified into three categories using a sensitivity analysis: 1) the parameters that affect the terminal voltage; 2) the parameters that affect the active power; and 3) the parameters that do not considerably affect either. A multistage genetic algorithm optimization is used to iteratively identify the parameters. To show the effectiveness and accuracy of the proposed method, it is applied to a single machine with a dc-type EXS connected to an infinite bus. Using the proposed method, 19 parameters of synchronous generator and its EXS are identified within four stages.
机译:本文提出了一种利用测量数据同时识别同步发电机及其励磁系统参数的新方法。这些测量可以由诸如数据采集系统或发电厂的故障记录仪之类的计量设备提供。由于智能电网能够使用相量测量单元提供同步测量,因此这些设备也可以提供所需数据。在提出的方法中,将EXS的参考电压视为输入信号,而将机器的端电压和输出有功功率视为输出信号。使用灵敏度分析将所需的参数分为三类:1)影响端子电压的参数; 2)影响有功功率的参数;和3)不会对两者产生重大影响的参数。使用多阶段遗传算法优化来迭代地识别参数。为了证明所提方法的有效性和准确性,将其应用于单机,该单机具有连接到无限总线的dc型EXS。利用所提出的方法,在四个阶段内确定了同步发电机及其EXS的19个参数。

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