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A Novel VSC HVDC Frequency Control Strategy based on Neural Network Power Estimation using ROCOF

机译:基于ROCOF的神经网络功率估计的新型VSC HVDC频率控制策略。

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This paper introduces a novel VSC HVDC frequency control strategy by Active Power Estimation. Although VSC HVDC has a much faster control speed than synchronous generator, frequency control of VSC is similar to that of governor. If VSC can use the fast-control character in frequency control, frequency stability can be improved. For fast control, proper power order is important and to estimate the power, this paper uses a neural network that solves the nonlinear relationship between input and output easily. To make quick control before the frequency reaches nadir, ROCOF is used as an input variable of the neural network. It can be seen that when the load of the system is greatly changed, the frequency fluctuation is significantly lowered when the VSC changes the output by the estimated power. Control of the VSC through the neural network is expected to enable faster frequency control than previously possible.
机译:本文介绍了一种基于有功功率估计的新型VSC HVDC频率控制策略。尽管VSC HVDC的控制速度比同步发电机快得多,但VSC的频率控制与调速器类似。如果VSC可以在频率控制中使用快速控制特性,则可以提高频率稳定性。为了实现快速控制,正确的功率阶数很重要,并且为了估计功率,本文使用了一个神经网络,可以轻松解决输入和输出之间的非线性关系。为了在频率达到最低点之前进行快速控制,将ROCOF用作神经网络的输入变量。可以看出,当系统的负载发生很大变化时,当VSC以估算的功率改变输出时,频率波动会大大降低。通过神经网络控制VSC有望实现比以前更快的频率控制。

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