Improving current and voltage transformers accuracy using artificial neural network

Haidar Samet; Farshid Nasrfard Jahromi; Arash Dehghani; Afsaneh Narimani

doi:10.1007/978-3-642-33409-2_45

Improving current and voltage transformers accuracy using artificial neural network

Haidar Samet, Farshid Nasrfard Jahromi, Arash Dehghani, Afsaneh Narimani

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Capacitive Voltage Transformers (CVTs) and Current Transformers (CTs) are commonly used in high voltage (HV) and extra high voltage (EHV) systems to provide signals for protecting and measuring devices. Transient response of CTs and CVTs could lead to relay mal-operation. To avoid these phenomena, this paper proposes an artificial neural network (ANN) method to correct CTs and CVTs secondary waveform distortions caused by the transients. PSCAD/EMTDC software is employed to produce the required voltage and current signals which are used for the training process and finally the results show that the proposed method is accurate and reliable in estimation of the CT primary current and the CVT primary voltage.

Original language	English
Title of host publication	Artificial Intelligence Applications and Innovations
Subtitle of host publication	8th IFIP WG 12.5 International Conference, AIAI 2012, Halkidiki, Greece, September 27-30, 2012, Proceedings, Part I
Place of Publication	Berlin
Publisher	Springer
Chapter	45
Pages	435-442
Number of pages	8
ISBN (Print)	9783642334085
DOIs	https://doi.org/10.1007/978-3-642-33409-2_45
Publication status	Published - 2012
Externally published	Yes
Event	8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012 - Halkidiki, Greece Duration: 27 Sept 2012 → 30 Sept 2012 Conference number: 8

Publication series

Name	IFIP Advances in Information and Communication Technology (IFIPAICT)
Volume	381
ISSN (Print)	1868-4238
ISSN (Electronic)	1861-2288

Conference

Conference	8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012
Abbreviated title	AIAI 2012
Country/Territory	Greece
City	Halkidiki
Period	27/09/12 → 30/09/12

Keywords

Artificial Neural Network (ANN)
Capacitive Voltage Transformers (CVTs)
Current Transformers (CTs)
Transient

Access to Document

10.1007/978-3-642-33409-2_45

Cite this

Samet, H., Jahromi, F. N., Dehghani, A., & Narimani, A. (2012). Improving current and voltage transformers accuracy using artificial neural network. In Artificial Intelligence Applications and Innovations: 8th IFIP WG 12.5 International Conference, AIAI 2012, Halkidiki, Greece, September 27-30, 2012, Proceedings, Part I (pp. 435-442). (IFIP Advances in Information and Communication Technology (IFIPAICT); Vol. 381). Springer. https://doi.org/10.1007/978-3-642-33409-2_45

Samet, Haidar ; Jahromi, Farshid Nasrfard ; Dehghani, Arash et al. / Improving current and voltage transformers accuracy using artificial neural network. Artificial Intelligence Applications and Innovations: 8th IFIP WG 12.5 International Conference, AIAI 2012, Halkidiki, Greece, September 27-30, 2012, Proceedings, Part I. Berlin : Springer, 2012. pp. 435-442 (IFIP Advances in Information and Communication Technology (IFIPAICT)).

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title = "Improving current and voltage transformers accuracy using artificial neural network",

abstract = "Capacitive Voltage Transformers (CVTs) and Current Transformers (CTs) are commonly used in high voltage (HV) and extra high voltage (EHV) systems to provide signals for protecting and measuring devices. Transient response of CTs and CVTs could lead to relay mal-operation. To avoid these phenomena, this paper proposes an artificial neural network (ANN) method to correct CTs and CVTs secondary waveform distortions caused by the transients. PSCAD/EMTDC software is employed to produce the required voltage and current signals which are used for the training process and finally the results show that the proposed method is accurate and reliable in estimation of the CT primary current and the CVT primary voltage.",

keywords = "Artificial Neural Network (ANN), Capacitive Voltage Transformers (CVTs), Current Transformers (CTs), Transient",

author = "Haidar Samet and Jahromi, {Farshid Nasrfard} and Arash Dehghani and Afsaneh Narimani",

year = "2012",

doi = "10.1007/978-3-642-33409-2_45",

language = "English",

isbn = "9783642334085",

series = "IFIP Advances in Information and Communication Technology (IFIPAICT)",

publisher = "Springer",

pages = "435--442",

booktitle = "Artificial Intelligence Applications and Innovations",

address = "Germany",

note = "8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012, AIAI 2012 ; Conference date: 27-09-2012 Through 30-09-2012",

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Samet, H, Jahromi, FN, Dehghani, A & Narimani, A 2012, Improving current and voltage transformers accuracy using artificial neural network. in Artificial Intelligence Applications and Innovations: 8th IFIP WG 12.5 International Conference, AIAI 2012, Halkidiki, Greece, September 27-30, 2012, Proceedings, Part I. IFIP Advances in Information and Communication Technology (IFIPAICT), vol. 381, Springer, Berlin, pp. 435-442, 8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012, Halkidiki, Greece, 27/09/12. https://doi.org/10.1007/978-3-642-33409-2_45

Improving current and voltage transformers accuracy using artificial neural network. / Samet, Haidar; Jahromi, Farshid Nasrfard; Dehghani, Arash et al.
Artificial Intelligence Applications and Innovations: 8th IFIP WG 12.5 International Conference, AIAI 2012, Halkidiki, Greece, September 27-30, 2012, Proceedings, Part I. Berlin: Springer, 2012. p. 435-442 (IFIP Advances in Information and Communication Technology (IFIPAICT); Vol. 381).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Improving current and voltage transformers accuracy using artificial neural network

AU - Samet, Haidar

AU - Jahromi, Farshid Nasrfard

AU - Dehghani, Arash

AU - Narimani, Afsaneh

N1 - Conference code: 8

PY - 2012

Y1 - 2012

N2 - Capacitive Voltage Transformers (CVTs) and Current Transformers (CTs) are commonly used in high voltage (HV) and extra high voltage (EHV) systems to provide signals for protecting and measuring devices. Transient response of CTs and CVTs could lead to relay mal-operation. To avoid these phenomena, this paper proposes an artificial neural network (ANN) method to correct CTs and CVTs secondary waveform distortions caused by the transients. PSCAD/EMTDC software is employed to produce the required voltage and current signals which are used for the training process and finally the results show that the proposed method is accurate and reliable in estimation of the CT primary current and the CVT primary voltage.

AB - Capacitive Voltage Transformers (CVTs) and Current Transformers (CTs) are commonly used in high voltage (HV) and extra high voltage (EHV) systems to provide signals for protecting and measuring devices. Transient response of CTs and CVTs could lead to relay mal-operation. To avoid these phenomena, this paper proposes an artificial neural network (ANN) method to correct CTs and CVTs secondary waveform distortions caused by the transients. PSCAD/EMTDC software is employed to produce the required voltage and current signals which are used for the training process and finally the results show that the proposed method is accurate and reliable in estimation of the CT primary current and the CVT primary voltage.

KW - Artificial Neural Network (ANN)

KW - Capacitive Voltage Transformers (CVTs)

KW - Current Transformers (CTs)

KW - Transient

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DO - 10.1007/978-3-642-33409-2_45

M3 - Conference contribution

SN - 9783642334085

T3 - IFIP Advances in Information and Communication Technology (IFIPAICT)

SP - 435

EP - 442

BT - Artificial Intelligence Applications and Innovations

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T2 - 8th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2012

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Samet H, Jahromi FN, Dehghani A, Narimani A. Improving current and voltage transformers accuracy using artificial neural network. In Artificial Intelligence Applications and Innovations: 8th IFIP WG 12.5 International Conference, AIAI 2012, Halkidiki, Greece, September 27-30, 2012, Proceedings, Part I. Berlin: Springer. 2012. p. 435-442. (IFIP Advances in Information and Communication Technology (IFIPAICT)). doi: 10.1007/978-3-642-33409-2_45

Improving current and voltage transformers accuracy using artificial neural network

Abstract

Publication series

Conference

Keywords

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