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Robustness and fault detection in power systems based on parameter-dependent Lyapunov functions

机译:基于参数依赖Lyapunov函数的电力系统的鲁棒性和故障检测

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In power systems, it is inevitable for faults and disturbances to happen, and the robust fault detection of power systems has become the focus of researchers in recent years. Since power systems do not generally have only one typical operating condition, the polytopic model provides a description of the uncertain system operation with a better physical meaning. To this end, the present study investigates the fault detection problem for uncertain polytopic power system model. In order to reduce the conservativeness of existing conditions, we present an efficient algorithm by generating homogeneous polynomial parameter-dependent Lyapunov functions of arbitrary degree on the uncertain parameters, which includes as special cases existing conditions for RFDF design. It can be established that as the degree of the polynomial increases, the number of LMIs and free variables increases and the test becomes less conservative. The methodology proposed can possibly be applied to relevant aspects such as improving the dynamic stability and robustness of power systems.
机译:在电力系统中,对于发生故障和扰动是不可避免的,并且电力系统的强大故障检测已成为近年来研究人员的重点。由于电力系统通常仅具有一个典型的操作条件,因此多种式模型提供了具有更好的物理意义的不确定系统操作的描述。为此,本研究研究了不确定多特电力系统模型的故障检测问题。为了降低现有条件的保守性,我们通过在不确定参数上生成任意度的均匀多项式参数依赖性Lyapunov函数来提出一种有效的算法,其包括作为RFDF设计的特殊情况现有条件。可以确定,随着多项式的程度增加,LMI的数量和自由变量的数量增加,并且测试变得更少保守。所提出的方法可能适用于相关方面,例如提高动力系统的动态稳定性和鲁棒性。

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