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A robust stochastic stability analysis approach for power system considering wind speed prediction error based on Markov model

机译:基于Markov模型的风速预测误差考虑风速预测误差的强大随机稳定性分析方法

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摘要

This paper proposes a robust stochastic stability analysis approach with partly unknown transition probability by considering the wind speed prediction error in power system. Firstly, taking this prediction error into account, based on Markov modeling theory, the stochastic dynamic model of wind power system with uncertain transition probability is developed. Secondly, according to the stochastic stability theory of Markov jump system, the transition probability of wind power system mode is divided into three cases: fully known, only known upper and lower bounds, and completely unknown. Then, by using linear matrix inequality (LMI) technology, a robust stochastic stability criterion with disturbance attenuation is obtained. Finally, test results show that the proposed analysis approach does not need to obtain the trajectory of the actual system operation parameters, and has the advantages of high computational efficiency.
机译:本文通过考虑电力系统中的风速预测误差,提出了一种坚固的随机稳定性分析方法,其具有部分未知的过渡概率。首先,基于Markov建模理论,考虑到这一预测错误,开发了过渡概率不确定风电系统的随机动态模型。其次,根据马尔可夫跳跃系统的随机稳定性理论,风电系统模式的过渡概率分为三种情况:完全已知,仅知道上限和下限,完全未知。然后,通过使用线性矩阵不等式(LMI)技术,获得具有干扰衰减的稳健随机稳定性标准。最后,测试结果表明,所提出的分析方法不需要获得实际系统操作参数的轨迹,并具有高计算效率的优点。

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