Application of genetic algorithm trained masterslave Neural Network for differential protection of power transformer

Vishwakarma, D. N.; Balaga, Harish; Nath, Harshit

doi:10.1109/icces.2014.7030950

Cited by 9 publications

(2 citation statements)

References 23 publications

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“…In the meantime, there are efforts to use artificial neural network to discriminate inrush currents and fault conditions [14,15], but these methods require training periods to fully achieve their functionality. In [16], an effective method that uses wavelet transform is proposed for indirect symmetrical phase shift transformers.…”

Section: Introductionmentioning

confidence: 99%

Setting-less transformer protection for ensuring security and dependability

Choi

Meliopoulos

2016

Electr Eng

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The "setting-less" protection approach is an innovative protection scheme with increased dependability and security. This method is based on dynamic state estimation, which continuously extracts the operating condition of a protection zone from real-time measurements and the protection zone dynamic model. The dynamic state estimation computes the probability that the measurements fit the dynamic model of the protection zone within the measurement accuracy via the Chi-square test. The probability represents the goodness of fit of measurements to the dynamic model of the protection zone. We refer to it as the confidence level that the protection zone is healthy. High confidence levels imply that the protection zone operates normally, while low confidence levels indicate that internal abnormalities/faults may have occurred. Note that the proposed method does not require coordination with other protection schemes which sometimes compromise security and/or dependability. In this paper, the setting-less protection approach is described and applied to transformer protection. The feasibility of the setting-less transformer protection is verified with numerical experiments of several case studies (e.g., transformer energization, external faults, internal faults, and high impedance faults). The method has been verified in the laboratory and there are plans for field testing.

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Section: Introductionmentioning

confidence: 99%

Setting-less transformer protection for ensuring security and dependability

Choi

Meliopoulos

2016

Electr Eng

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“…The authors of [4] considered the differential protection of a transformer with multilevel ANN. One ANN detects damage, and the other is used as a damage classifier.…”

Section: Introductionmentioning

confidence: 99%

Development and research of an intelligent control system and protection of electrical network equipment

Bashirov,

Vildanov,

Sabiryanova

et al. 2024

E3S Web Conf.

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The key element of an intelligent energy system with an active-adaptive network is relay protection, designed to ensure uninterrupted and stable operation of the energy system. The goal of the work is the development and research of intelligent control systems, protection and automation of electrical networks. Research has been carried out on an intelligent security system to determine the boundaries of restrictions in the use of artificial intelligence. The authors supplemented the existing complex with physical models of the power supply system with a digital twin, an artificial neural network, and studied the complex in order to answer some questions about the use of a neural network in relay protection. An iterative approach to software development, supervised machine learning method, and Python programming language were used. Pychram Community Edition was chosen as the integrated development environment. Intelligent system software has been developed, including a digital twin, an executive part and a neural network model, which makes it possible to recognize types of short circuits in the electrical network. The works of domestic and foreign authors on this topic are considered.

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Introduction to Power Transformer Protection

Patel¹,

Chothani

2020

Power Systems

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Application of genetic algorithm trained masterslave Neural Network for differential protection of power transformer

Cited by 9 publications

References 23 publications

Setting-less transformer protection for ensuring security and dependability

Setting-less transformer protection for ensuring security and dependability

Development and research of an intelligent control system and protection of electrical network equipment

Introduction to Power Transformer Protection

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