Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models

Adaptive protection schemes (APS) have gained prominence in maintaining the integrity of overcurrent relay (OCR) settings in reconfigurable networks. While many APSs rely on supervisory control and data acquisition systems, they are very expensive and expose the system to vulnerabilities arising fro...

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Main Authors: Wong, Junying, Tan, Chiakwang, Abd Rahim, Nasrudin, Tan, Rodney H. G.
Format: Article
Published: Institute of Electrical and Electronics Engineers 2024
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Online Access:http://eprints.um.edu.my/45709/
https://doi.org/10.1109/TPWRD.2023.3330730
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spelling my.um.eprints.457092024-11-08T08:41:08Z http://eprints.um.edu.my/45709/ Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models Wong, Junying Tan, Chiakwang Abd Rahim, Nasrudin Tan, Rodney H. G. TK Electrical engineering. Electronics Nuclear engineering Adaptive protection schemes (APS) have gained prominence in maintaining the integrity of overcurrent relay (OCR) settings in reconfigurable networks. While many APSs rely on supervisory control and data acquisition systems, they are very expensive and expose the system to vulnerabilities arising from communication failures. Recent studies have proposed communication-less APSs to address this issue by relying on data-mining algorithms equipped with real-time fault voltage-current information. However, the OCR settings are computed and updated as the fault occurs, inevitably causing prolonged OCR tripping in these schemes. This contradicts with the APS' original purpose of minimizing OCR operation time and consequent equipment damage. Thus, a load flow-based APS that addresses this flaw is proposed to achieve primary-backup OCR coordination in a highly reconfigurable system. Network topologies are first categorized into OCR setting groups via clustering analysis. A nonparametric probability model is developed to evaluate the probability of network topologies at a measured load flow. Then, a machine learning model deployed in a local controller selects the correct setting groups based on the calculated probabilities. The proposed APS achieves high accuracies and low OCR operating times in the IEEE 33-bus test distribution system under varying load conditions and network topologies. Institute of Electrical and Electronics Engineers 2024-02 Article PeerReviewed Wong, Junying and Tan, Chiakwang and Abd Rahim, Nasrudin and Tan, Rodney H. G. (2024) Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models. IEEE Transactions on Power Delivery, 39 (1). pp. 202-209. ISSN 0885-8977, DOI https://doi.org/10.1109/TPWRD.2023.3330730 <https://doi.org/10.1109/TPWRD.2023.3330730>. https://doi.org/10.1109/TPWRD.2023.3330730 10.1109/TPWRD.2023.3330730
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Wong, Junying
Tan, Chiakwang
Abd Rahim, Nasrudin
Tan, Rodney H. G.
Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models
description Adaptive protection schemes (APS) have gained prominence in maintaining the integrity of overcurrent relay (OCR) settings in reconfigurable networks. While many APSs rely on supervisory control and data acquisition systems, they are very expensive and expose the system to vulnerabilities arising from communication failures. Recent studies have proposed communication-less APSs to address this issue by relying on data-mining algorithms equipped with real-time fault voltage-current information. However, the OCR settings are computed and updated as the fault occurs, inevitably causing prolonged OCR tripping in these schemes. This contradicts with the APS' original purpose of minimizing OCR operation time and consequent equipment damage. Thus, a load flow-based APS that addresses this flaw is proposed to achieve primary-backup OCR coordination in a highly reconfigurable system. Network topologies are first categorized into OCR setting groups via clustering analysis. A nonparametric probability model is developed to evaluate the probability of network topologies at a measured load flow. Then, a machine learning model deployed in a local controller selects the correct setting groups based on the calculated probabilities. The proposed APS achieves high accuracies and low OCR operating times in the IEEE 33-bus test distribution system under varying load conditions and network topologies.
format Article
author Wong, Junying
Tan, Chiakwang
Abd Rahim, Nasrudin
Tan, Rodney H. G.
author_facet Wong, Junying
Tan, Chiakwang
Abd Rahim, Nasrudin
Tan, Rodney H. G.
author_sort Wong, Junying
title Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models
title_short Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models
title_full Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models
title_fullStr Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models
title_full_unstemmed Communication-Less Adaptive Overcurrent Protection for Highly Reconfigurable Systems Based on Nonparametric Load Flow Models
title_sort communication-less adaptive overcurrent protection for highly reconfigurable systems based on nonparametric load flow models
publisher Institute of Electrical and Electronics Engineers
publishDate 2024
url http://eprints.um.edu.my/45709/
https://doi.org/10.1109/TPWRD.2023.3330730
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score 13.222552