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Nonlinear simulation of Kaplan turbine regulating system based on RBF networks

机译:基于RBF网络的Kaplan汽轮机调节系统非线性仿真。

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To simulate the hydroelectric power unit dynamic behavior as accurately as possible, the nonlinear characteristics of hydroturbine is considerable. This paper presents a nonlinear model of double regulated Kaplan turbine. Radial Basis Function (RBF) networks are applied to process the synthetic characteristic curve of Kaplan turbine. This improves the fitted data's accuracy. Based on this, the nonlinear Kaplan turbine regulating system model is developed in Simulink. The digital simulations of three cases for an actual hydroelectric power plant in China were performed, and the difference between nonlinear and linear Kaplan turbine regulating system model was analyzed. The results indicate that in small fluctuate transient process, the two models' simulation results are in good agreement, but in large fluctuate transient process, the nonlinear characteristics is not negligible and the two models' simulation results are deviate from each other seriously. The nonlinear model based on RBF networks is more accurate to reflect the regulating system's nonlinear dynamic process.
机译:为了尽可能准确地模拟水力发电机组的动态行为,水轮机的非线性特性相当可观。本文提出了双调节卡普兰汽轮机的非线性模型。径向基函数(RBF)网络用于处理Kaplan涡轮机的综合特性曲线。这提高了拟合数据的准确性。基于此,在Simulink中开发了非线性Kaplan涡轮调节系统模型。对中国某实际水力发电厂的三种情况进行了数字仿真,并分析了非线性和线性Kaplan水轮机调节系统模型之间的差异。结果表明,在小波动瞬态过程中,两个模型的仿真结果吻合良好,但在大波动瞬态过程中,非线性特性不可忽略,并且两个模型的仿真结果严重偏离。基于RBF网络的非线性模型更准确地反映了调节系统的非线性动力学过程。

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