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Parameter identification of a nonlinear model of hydraulic turbine governing system with an elastic water hammer based on a modified gravitational search algorithm

机译:基于改进重力搜索算法的弹性水锤水轮机调节系统非线性模型参数辨识

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摘要

The hydraulic turbine governing system (HTGS) is a crucial control system of hydroelectric generating units (HGUs). Parameter identification of HTGS is an important issue for the modeling and control of HGUs. The parameter identification problem of HTGS is more difficult if the elastic water hammer model is considered in the system, and existing algorithms are not effective to solve it To solve this new problem, a modified gravitational search algorithm (MGSA) has been proposed in which modifications have been made to improve the performance of the GSA from two aspects. First the constant attenuation factor is replaced by a hyperbolic function to generate a better gravitational constant to balance the global exploration and local exploitation during different searching stages. Second, agent mutation is introduced to increase the diversity of agents and to strengthen the ability to jump out of the local minima of the GSA. The performance of the MGSA has been verified by 13 typical benchmark problems, and the experimental results and statistical analysis demonstrate that the proposed MGSA significantly outperforms the standard GSA and some other popular optimization algorithms. The MGSA is then employed in the parameter identification of a nonlinear model of HTGS with an elastic water hammer, and the experimental results indicate that MGSA locates more precise parameter values than the compared methods.
机译:水轮机调节系统(HTGS)是水力发电机组(HGU)的关键控制系统。 HTGS的参数识别是HGU建模和控制的重要问题。如果在系统中考虑弹性水锤模型,则HTGS的参数识别问题将更加困难,并且现有算法无法有效解决该问题。为解决这一新问题,提出了一种改进的重力搜索算法(MGSA),其中从两个方面改进了GSA的性能。首先,恒定的衰减因子由双曲线函数代替,以生成更好的引力常数,以平衡不同搜索阶段的整体勘探和局部开采。其次,引入代理突变以增加代理的多样性并增强跳出GSA局部最小值的能力。 MGSA的性能已通过13个典型基准问题得到了验证,实验结果和统计分析表明,所提出的MGSA明显优于标准GSA和其他一些流行的优化算法。然后将MGSA用于带有弹性水锤的HTGS非线性模型的参数识别中,实验结果表明MGSA比比较方法定位的参数值更精确。

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