基于轨迹特征根的系统暂态稳定判断与扰动类型筛选方法

发布时间：2018-02-08 09:48

本文关键词： 电力系统暂态稳定轨迹特征根事故筛选波动方差　出处：《西南交通大学》2017年硕士论文　论文类型：学位论文

【摘要】：电力系统的安全稳定运行与否直接影响到社会经济的发展,实际中电力系统不可避免地遭受各种扰动。若不能够判断出扰动后系统的暂态稳定性以及识别扰动的类型,及时采取相应措施进行处理,恢复正常供电,故障范围可能会扩大,进而引发电力系统大事故的产生。更严重的情况下造成系统振荡甚至解列,将产生不可估量的经济损失和难以预测的社会影响。为了准确地判断扰动后系统暂态稳定性并对扰动的类型进行筛选,在深入研究已有方法的基础上,针对已有方法存在的不足,本文尝试用扰动后系统轨迹特征根的波动特性进行系统暂态稳定性判断和扰动类型筛选,并对其中的关键性问题进行分析和讨论。首先,建立高阶系统线性化模型,充分考虑调速器和励磁系统等系统主要元件对系统线性化模型的影响。调速器和励磁系统模型在线性化处理时考虑到模型的复杂性,尝试一种利用拉普拉斯逆变换实现复杂模块模型在非平衡点处的线性化处理方法。其次,将扰动后系统轨迹特征根的波动情况与对应扰动下发电机相对功角曲线判断得出的系统暂态稳定性结果进行比较,发现系统扰动后暂态稳定时,轨迹特征根衰减性振荡,并最终收敛于小范围的波动。系统扰动后如果暂态不稳定,则轨迹特征根无规律振荡,并无收敛趋势。根据这个规律,本文提出了一种基于扰动后系统轨迹特征根的暂态稳定性判断方法,该方法判定系统遭受预想事故的暂态稳定性虽然耗时较长,但是由于轨迹特征根曲线是综合所有变量求取的结果,包括发电机功角、机端电压等变量,因此准确性较传统单一变量判断系统暂态稳定性有较大的提高,适用于电力规划和运行调度的离线暂态稳定性分析。最后,通过分析发现扰动的大小和类型对轨迹特征根的影响程度各不相同,尤其是轨迹特征根的波动范围有明显差别。有害扰动和无害扰动作用下系统轨迹特征根波动特性之间的差别尤为显著,引用方差对扰动后的轨迹特征根曲线进行振荡和离散程度的量化分析,并以此量化指标为依据,根据系统轨迹特征根曲线的波动方差与扰动类型的对应关系,本文提出一种基于扰动后系统轨迹特征根波动方差的扰动类型识别方法。在解决快速性问题上,该方法采用扰动发生后的第一个摇摆周期作为时间截面,计算该时间截面轨迹特征根的波动方差。并通过算例进行验证,结果表明,预想扰动设置的类型与扰动识别区识别的结果相一致,论证了这种方法能够有效满足系统暂态分析中对扰动类型快速、准确筛选的要求。
[Abstract]:The safe and stable operation of power system has a direct impact on the development of social economy. In practice, the power system is inevitably subjected to various disturbances. If the transient stability of the system after disturbance can not be judged and the type of disturbance can be identified, Timely measures should be taken to deal with it, restore normal power supply, and the range of faults may be enlarged, which may lead to the occurrence of major accidents in the power system. In more serious cases, the system will oscillate or even be desegregated. In order to accurately judge the transient stability of the system after disturbance and screen out the types of disturbance, based on the existing methods, In view of the shortcomings of the existing methods, this paper attempts to use the characteristic root of the system trajectory after disturbance to judge the transient stability of the system and to screen out the types of disturbance. The key problems are analyzed and discussed. The linearization model of higher-order system is established, and the influence of the main components of the governor and excitation system on the linearization model of the system is fully considered. The complexity of the model is taken into account when the governor and the excitation system model are linearized. This paper tries to use Laplace inverse transform to realize the linearization of complex module model at the non-equilibrium point. Secondly, By comparing the fluctuation of the system trajectory characteristic root after disturbance with the transient stability of the system determined by the relative power angle curve of the generator under the corresponding disturbance, it is found that the trajectory characteristic root attenuates oscillation when the system is transient stability after disturbance. And finally converges to a small range of fluctuations. If the system is disturbed by transient instability, the trajectory characteristic root oscillates irregularly and has no convergence trend. In this paper, a method of judging transient stability based on the characteristic root of the system trajectory after disturbance is proposed. This method takes a long time to judge the transient stability of the system subjected to the expected accident. However, because the trajectory characteristic root curve is the result of synthesizing all variables, such as generator power angle, terminal voltage and so on, the accuracy of the trajectory characteristic root curve is much higher than that of the traditional single variable in judging the transient stability of the system. It is suitable for off-line transient stability analysis of power planning and operation dispatching. Finally, it is found that the magnitude and type of disturbance have different influence on the trajectory characteristic root. Especially, the fluctuation range of trajectory characteristic root is obviously different, especially between harmful disturbance and harmless disturbance. The oscillation and dispersion degree of the trajectory characteristic root curve after disturbance is analyzed quantitatively by using variance, and based on the quantization index, according to the relation between the fluctuation variance of the characteristic root curve and the type of disturbance, In this paper, a disturbance type identification method based on the variance of the characteristic root fluctuation of the trajectory of the perturbed system is proposed. In order to solve the problem of rapidity, the first rocking period after disturbance is used as the time section. The fluctuation variance of the characteristic root of the track of the time section is calculated and verified by an example. The results show that the type of the preconceived disturbance is consistent with the result of the identification of the disturbance. It is demonstrated that this method can effectively meet the requirement of fast and accurate screening of disturbance types in transient analysis of systems.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM712

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