Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network

Wen Jun Tang; Hong Tzer Yang

doi:10.1109/EEEIC.2017.7977738

Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network

Wen Jun Tang
, Hong Tzer Yang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

Abstract

Owing to development of renewable energy and environmental protection issues, distributed generations (DGs) have become a trend. In addition, fault current limiters (FCLs) may be installed to prevent the short circuit current from exceeding the capacity of the power apparatus. Nevertheless, some issues appear, simultaneously, the most important among which is the mis-coordination of the protection system. This paper proposes overcurrent protection strategies for distribution systems with DGs and FCLs. Via the proposed approach, the relays with communication ability can determine their own operating states from the operation setting decision tree and topology-adaptive Neural Network model based on the data processed by Fast Fourier Transformer (FFT). The performance and effectiveness of the proposed protection strategies are verified via the simulation results obtained from different system topologies with/without DGs, FCLs, and load variation.

Original language	English
Title of host publication	Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538639160
DOIs	https://doi.org/10.1109/EEEIC.2017.7977738
Publication status	Published - 2017 Jul 12
Event	17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017 - Milan, Italy Duration: 2017 Jun 6 → 2017 Jun 9

Publication series

Name	Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017

Other

Other	17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017
Country/Territory	Italy
City	Milan
Period	17-06-06 → 17-06-09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Electrical and Electronic Engineering
Industrial and Manufacturing Engineering
Environmental Engineering

Access to Document

10.1109/EEEIC.2017.7977738

Cite this

Tang, W. J., & Yang, H. T. (2017). Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network. In Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017 Article 7977738 (Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EEEIC.2017.7977738

Tang, Wen Jun ; Yang, Hong Tzer. / Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network. Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017. Institute of Electrical and Electronics Engineers Inc., 2017. (Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017).

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title = "Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network",

abstract = "Owing to development of renewable energy and environmental protection issues, distributed generations (DGs) have become a trend. In addition, fault current limiters (FCLs) may be installed to prevent the short circuit current from exceeding the capacity of the power apparatus. Nevertheless, some issues appear, simultaneously, the most important among which is the mis-coordination of the protection system. This paper proposes overcurrent protection strategies for distribution systems with DGs and FCLs. Via the proposed approach, the relays with communication ability can determine their own operating states from the operation setting decision tree and topology-adaptive Neural Network model based on the data processed by Fast Fourier Transformer (FFT). The performance and effectiveness of the proposed protection strategies are verified via the simulation results obtained from different system topologies with/without DGs, FCLs, and load variation.",

author = "Tang, \{Wen Jun\} and Yang, \{Hong Tzer\}",

note = "Funding Information: This work was supported by the Ministry of Science and Technology, Taiwan, under Grant MOST 106-3113-E-006-010. Publisher Copyright: {\textcopyright} 2017 IEEE.; 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017 ; Conference date: 06-06-2017 Through 09-06-2017",

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doi = "10.1109/EEEIC.2017.7977738",

language = "English",

series = "Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Tang, WJ & Yang, HT 2017, Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network. in Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017., 7977738, Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017, Institute of Electrical and Electronics Engineers Inc., 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017, Milan, Italy, 17-06-06. https://doi.org/10.1109/EEEIC.2017.7977738

Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network. / Tang, Wen Jun; Yang, Hong Tzer.
Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7977738 (Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network

AU - Tang, Wen Jun

AU - Yang, Hong Tzer

PY - 2017/7/12

Y1 - 2017/7/12

N2 - Owing to development of renewable energy and environmental protection issues, distributed generations (DGs) have become a trend. In addition, fault current limiters (FCLs) may be installed to prevent the short circuit current from exceeding the capacity of the power apparatus. Nevertheless, some issues appear, simultaneously, the most important among which is the mis-coordination of the protection system. This paper proposes overcurrent protection strategies for distribution systems with DGs and FCLs. Via the proposed approach, the relays with communication ability can determine their own operating states from the operation setting decision tree and topology-adaptive Neural Network model based on the data processed by Fast Fourier Transformer (FFT). The performance and effectiveness of the proposed protection strategies are verified via the simulation results obtained from different system topologies with/without DGs, FCLs, and load variation.

AB - Owing to development of renewable energy and environmental protection issues, distributed generations (DGs) have become a trend. In addition, fault current limiters (FCLs) may be installed to prevent the short circuit current from exceeding the capacity of the power apparatus. Nevertheless, some issues appear, simultaneously, the most important among which is the mis-coordination of the protection system. This paper proposes overcurrent protection strategies for distribution systems with DGs and FCLs. Via the proposed approach, the relays with communication ability can determine their own operating states from the operation setting decision tree and topology-adaptive Neural Network model based on the data processed by Fast Fourier Transformer (FFT). The performance and effectiveness of the proposed protection strategies are verified via the simulation results obtained from different system topologies with/without DGs, FCLs, and load variation.

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M3 - Conference contribution

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T3 - Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017

BT - Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017

Y2 - 6 June 2017 through 9 June 2017

ER -

Tang WJ, Yang HT. Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network. In Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 7977738. (Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017). doi: 10.1109/EEEIC.2017.7977738

Self-adaptive protection strategies for distribution system with DGs and FCLs based on data mining and neural network

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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