Design and Evaluation a Distance Relay Model Based On Artificial Neural Networks (ANN)

Alashter, Mossa A.; Mrehel, Omar G.; Shamekh, Abdunnaser S.

doi:10.1109/energycon48941.2020.9236490

Cited by 8 publications

(4 citation statements)

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“…Most previous researchers overlooked the fault which happens when one or two lines are open as in Figure 9a,b, and as shown in Figure 10, (1-6) and (7)(8)(9)(10)(11)(12), respectively, which is the result of a system flaw. Thus, the signal cut-off, as shown in Figure 9, obviously, is a change at a specific time, which the Fast Fourier Transform is unable to distinguish, because the FFT represents the signal value and frequency without mentioning time.…”

Section: Introduction To Results and Discussionmentioning

confidence: 99%

“…However, such approaches are seen to be insufficient, particularly the extended time required to detect and isolate faults. As a consequence, a variety of recent theories and algorithms have been used to improve the protection of electric power systems and particularly transmission lines (TLs) [6][7][8], which are more prone to failures due to their length and their outside exposure. A TL protection scheme must be comprehensive and general, and it should apply to the majority, if not all, types of transmission systems, such as those with power factor correction, compensators, load, transformers, and other components.…”

Section: Introductionmentioning

confidence: 99%

“…Studies regarding transmission line protection are based on either a single theory [7,11,12,[19][20][21][22][23] such as ANN, WT, SVM, and others, or a combination of theories [24][25][26][27][28][29] such as (WT and ANN), (WT combined with fuzzy logic), (DWT, FT and ANN), and others. Artificial Intelligence (AI)-based transmission line protection is the most widely used approach nowadays due to its comprehensive outlook and efficiency.…”

Section: Introductionmentioning

confidence: 99%

“…Artificial Intelligence (AI)-based transmission line protection is the most widely used approach nowadays due to its comprehensive outlook and efficiency. Artificial Neural Network (ANN)-based algorithms have the capability of training and learning the system's behavior in a variety of settings with great outcomes [7,24,[30][31][32]. Support Vector Machine (SVM) is also used for fault diagnosis, in which it can detect faults, but the results can be severely affected with noisy signals [33].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fault Detection on Power Transmission Line Based on Wavelet Transform and Scalogram Image Analysis

Altaie,

Majeed,

Abderrahim

et al. 2023

Energies

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Given the massive increase in demand for electrical energy, particularly owing to global climate change and population expansion, as well as the development of complicated electrical systems due to the urgent need for a sophisticated component to enhance power delivery, it becomes important to adopt a smart and contemporary approach that is also appropriate for the aim of protecting transmission lines (TLs) and ensuring the continuous delivery of electric power to customers. Consequently, a unique and highly reliable approach for identifying faults in TLs is presented in this work, which employs Wavelet Transform and is evaluated using Matlab simulation. Wavelets of various kinds were utilized to demonstrate their dependability. Furthermore, utilizing this approach has shown itself to be highly successful and has yielded spectacular results even when it is used on a complicated electrical network. Moreover, many types of faults were presented and afterward evaluated and verified for the network in various settings, which also demonstrated their potential to recognize faults within a relatively short space of time. This innovation will alter the idea of fault detection by providing a complete and integrated model for detecting faults in a TL, and it may be regarded as a revolution in the renewal of core principles in TL protection.

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