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Application of optimization control based on RBF neural network in VSC-HVDC

机译:基于RBF神经网络的优化控制在VSC-HVDC中的应用

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An appropriate operating principle of voltage source converter based high voltage direct current (VSC-HVDC) is able to further affect the sensitivity to voltage unbalance. The new HVDC system based on voltage source has broadened application prospect for its beneficial characteristics compared with the traditional DC transmission system. In the paper, a simple and effective simulation model of VSC-HVDC system is presented to improve the dynamic performances. The traditional PI controller of the two-level VSC-HVDC system is implemented, and then an optimal controller based on the radial basis function (RBF) neural network is designed to further control VSC-HVDC system. The simulation results show that the optimized controller based on the radial basis function can effectively optimize the control parameters of the VSC-HVDC system, and the response characteristics of the system are better than before.
机译:基于电压源转换器的高压直流电(VSC-HVDC)的适当工作原理能够进一步影响对电压不平衡的敏感性。与传统的直流输电系统相比,基于电压源的新型高压直流输电系统以其有益的特性而具有广阔的应用前景。本文提出了一种简单有效的VSC-HVDC系统仿真模型,以提高其动态性能。实现了传统的两级VSC-HVDC系统的PI控制器,然后设计了基于径向基函数(RBF)神经网络的最优控制器来进一步控制VSC-HVDC系统。仿真结果表明,基于径向基函数的优化控制器可以有效地优化VSC-HVDC系统的控制参数,系统的响应特性优于以往。

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