摘要
提出了一种新的故障跟踪估计器来诊断高压直流输电(HVDC)系统中的故障。考虑到随机噪声对测量结果的影响,首先采用协同(Consensus)滤波器对HVDC系统的输出滤波,然后根据HVDC状态方程引入一个新的参数——虚拟故障,来构建故障跟踪估计器。根据预测控制中的滚动优化思想,选取优化时域,并根据故障跟踪估计器的输出电压和HVDC实际电压的差,通过反复迭代运算来调节虚拟故障,使虚拟故障逼近系统中实际发生的故障,从而对故障进行分类。与基于神经网络等方法的故障诊断不同的是,该设计方法不但可以检测出故障,还可以估计出故障函数,针对不同类型的故障也可以很好地进行诊断。最后针对不同类型故障的仿真结果表明了该算法的可行性和有效性。
A novel fault tracking approximator for fault diagnosis scheme of high voltage direct current transmission （HVDC） system is proposed. A consensus filter is used to mitigate the random noise at the d. c. side of HVDC. According to the HVDC state space equation, a new parameter, i.e. virtual fault, is introduced to represent the actual fault to construct the fault tracking approximator. Based on the predictive theory, an optimization time span is then chosen. Using the iterative algorithm, virtual fault is adjusted to approximate actual one in terms of the difference between outputs of the fault tracking approximator and the actual system. Different from those traditional fault diagnostic methods grounded on neural networks or support vector machines, the algorithm proposed can not only detect the system faults, estimate the fault function, but diagnose different sorts of faults. Finally, simulation results show the feasibility and effectiveness of the approach proposed.
出处
《电力系统自动化》
EI
CSCD
北大核心
2007年第16期57-61,共5页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(60574081)~~
关键词
高压直流输电系统
协同滤波器
故障诊断
故障跟踪估计器
预测控制
迭代运算
high voltage direct current transmission （HVDC） system
consensus filter
fault diagnosis
fault tracking approximator
predictive control
iterative algorithm
