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Identification of hydraulic turbine governor system parameters based on Bacterial Foraging Optimization Algorithm

机译:基于细菌觅食优化算法的水轮机调速器系统参数辨识

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Hydraulic turbine generating unit plays an important role in power system. An accurate hydraulic turbine governor system model is essential to analyze its stability and dynamic performance. In order to identify the parameters of the hydraulic turbine governor system model, a new approach of Bacterial Foraging Optimization Algorithm (BFOA) is introduced in this study. To improve the precision of the identification process, a modified objective function is proposed based on the measurement of gate opening, mechanical torque and generator speed from a simulated model. The improved objective function (IOF) and the conventional objective function (COF) are used in the identification and two sets of parameters are derived and compared. The results show that BFOA is effective in identification of hydraulic turbine governor system and parameters derived from the modified objective function have a higher accuracy.
机译:水轮机发电机组在电力系统中起着重要的作用。准确的水轮机调速器系统模型对于分析其稳定性和动态性能至关重要。为了识别水轮机调速系统模型的参数,提出了一种新的细菌觅食优化算法(BFOA)。为了提高识别过程的精度,基于模拟模型对闸门开度,机械转矩和发电机转速的测量结果,提出了一种改进的目标函数。改进的目标函数(IOF)和常规目标函数(COF)用于识别,并导出和比较两组参数。结果表明,BFOA在识别水轮机调速系统中是有效的,而从修正目标函数推导出的参数具有较高的精度。

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