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High-voltage transmission lines , transient an‎d permanent faults , single-phase reclosure , intrinsic components of fault signals , an‎d Empirical Mode Decomposition method

Automatic adaptive single-phase reclosing method to improving the stability of power transmission networks

مهندسي برق

In power transmission networks, the occurrence of faults is one of the most significant challenges that seriously threaten the stability an‎d reliability of the system. With the increasing expansion of energy resources, the dynamic behavior of power systems has become more complex, an‎d the likelihood of various types of transient an‎d permanent faults has increased. Accurate fault type detection an‎d timely management of the process for disconnecting an‎d reconnecting protective equipment directly impact the stability, quality, an‎d continuity the power supply. In particular, the development of adaptive an‎d intelligent solutions for single-phase reconnection plays a key role in improving the performance of modern networks. On the other han‎d, traditional methods for detecting an‎d managing faults often come with limitations, including accuracy, speed, an‎d compatibility with system operating conditions, which amplifies the need for innovative solutions. Therefore, in this thesis, a new adaptive method is proposed for detecting transient an‎d permanent faults an‎d determining the optimal time for disconnecting an‎d reconnecting protective switches based on Empirical Mode Decomposition (EMD). The main idea of the proposed method is to extract the intrinsic components of fault signals an‎d analyze their derivatives to quickly an‎d accurately assess the transient behavior of the system. The intrinsic components are identified as signal parts with different frequencies an‎d dynamics, an‎d whose behavior analysis , especially at the moments of fault occurrences, enables the identification of points of instability an‎d system status changes. By examining the maximum an‎d minimum values of the derivatives of the intrinsic components, the exact timing of fault occurrence an‎d network stability recovery can be determined automatically. The simulation results in the EMTP-Works an‎d MATLAB software environments indicate that this method not only possesses high accuracy an‎d speed for distinguishing transient an‎d permanent faults but also provides suitable capabilities in predicting an‎d optimizing the reconnection timing of switches. Thus, the application of the proposed method can be an effective step towards increasing stability, reducing outages, an‎d improving fault management in modern power systems.

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