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A new converter fault discrimination method for a 12-pulse high-voltage direct current system based on wavelet transform and Hidden Markov Models

机译:基于小波变换和隐马尔可夫模型的12脉冲高压直流系统换流器故障判别新方法

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The progressive development in high-voltage direct current (HVDC) transmission enhances the need to implement an efficient protection scheme to distinguish the minimum faulty part of the system and to relieve the stressed equipment. This paper proposes a new classification method based on Hidden Markov Models and wavelet transform to discriminate HVDC converter faults. In the proposed technique, probabilistic characteristics of signals discriminate fault signals without any deterministic index, so more flexible classification in different system conditions is achieved. Based on this method, high-speed protection decisions with small computational time could be performed in approximately 5 ms for severe system faults, and in 12.5 ms for faults that are restricted by protective control decision. PSCAD/EMTDC software simulations demonstrate suitable performance of this scheme for different fault types and system conditions in the International Council for Large Electric Systems (CIGRE) HVDC benchmark. All simulation results validate the stability and robustness of proposed scheme in different conditions, such as noisy systems.
机译:高压直流(HVDC)输电的逐步发展增加了实施有效保护方案的必要性,以区分系统的最小故障部分并缓解压力设备。提出了一种基于隐马尔可夫模型和小波变换的新方法,用于判别高压直流输电线路的故障。所提出的技术中,信号的概率特性可以在没有任何确定性指标的情况下区分故障信号,因此可以在不同的系统条件下实现更加灵活的分类。基于此方法,对于严重的系统故障,可以在大约5 ms内执行计算时间短的高速保护决策,对于受保护性控制决策限制的故障,可以在12.5 ms内执行。 PSCAD / EMTDC软件仿真在国际大型电气系统理事会(CIGRE)HVDC基准测试中证明了该方案针对不同故障类型和系统条件的合适性能。所有仿真结果都验证了所提出方案在不同条件下(例如噪声系统)的稳定性和鲁棒性。

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