Transient security assessment for power system stability: a review on artificial intelligence approach
The growth of large interconnected electricity networks requires a high degree of security for normal operation. This paper attempts to overview several available techniques for assessing the Transient Security Assessment (TSA) of a power system. Different algorithms are explained in details (Static...
| Main Authors: | , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2009
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/47756/1/Transient%20security%20assessment%20for%20power%20system%20stability%20a%20review%20on%20artificial%20intelligence%20approach.pdf |
| _version_ | 1796974850423652352 |
|---|---|
| author | Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Jasni, Jasronita Mariun, Norman |
| author_facet | Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Jasni, Jasronita Mariun, Norman |
| author_sort | Al-Masri, Ahmed Naufal A. |
| collection | UPM |
| description | The growth of large interconnected electricity networks requires a high degree of security for normal operation. This paper attempts to overview several available techniques for assessing the Transient Security Assessment (TSA) of a power system. Different algorithms are explained in details (Static and Dynamic Security Assessment) with the uses of Artificial Intelligent (AI) method. Transient effects can be roughly described as undesired voltage/ current that may result a contingencies in the power system. However, it is only considered lightning and switching as the main causes of TSA. In this proposed method, Artificial Neural Network (ANN) and Fuzzy techniques are able to use in term of classification, prediction and to determine the system security status. Time domain analysis is performed for each credible contingency using signal processing method; than an AI model is proposed for the TSA analysis. The novelty of the proposed approach is that the fast ability to detect and classify any disturbance (lightning (or) switching) in the electric power system using AI techniques. |
| first_indexed | 2024-03-06T09:03:01Z |
| format | Conference or Workshop Item |
| id | upm.eprints-47756 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:03:01Z |
| publishDate | 2009 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-477562016-07-14T09:41:35Z http://psasir.upm.edu.my/id/eprint/47756/ Transient security assessment for power system stability: a review on artificial intelligence approach Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Jasni, Jasronita Mariun, Norman The growth of large interconnected electricity networks requires a high degree of security for normal operation. This paper attempts to overview several available techniques for assessing the Transient Security Assessment (TSA) of a power system. Different algorithms are explained in details (Static and Dynamic Security Assessment) with the uses of Artificial Intelligent (AI) method. Transient effects can be roughly described as undesired voltage/ current that may result a contingencies in the power system. However, it is only considered lightning and switching as the main causes of TSA. In this proposed method, Artificial Neural Network (ANN) and Fuzzy techniques are able to use in term of classification, prediction and to determine the system security status. Time domain analysis is performed for each credible contingency using signal processing method; than an AI model is proposed for the TSA analysis. The novelty of the proposed approach is that the fast ability to detect and classify any disturbance (lightning (or) switching) in the electric power system using AI techniques. IEEE 2009 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/47756/1/Transient%20security%20assessment%20for%20power%20system%20stability%20a%20review%20on%20artificial%20intelligence%20approach.pdf Al-Masri, Ahmed Naufal A. and Ab Kadir, Mohd Zainal Abidin and Hizam, Hashim and Jasni, Jasronita and Mariun, Norman (2009) Transient security assessment for power system stability: a review on artificial intelligence approach. In: 2009 IEEE Student Conference on Research and Development (SCOReD 2009), 16-18 Nov. 2009, UPM, Serdang, Selangor. (pp. 371-375). 10.1109/SCORED.2009.5442996 |
| spellingShingle | Al-Masri, Ahmed Naufal A. Ab Kadir, Mohd Zainal Abidin Hizam, Hashim Jasni, Jasronita Mariun, Norman Transient security assessment for power system stability: a review on artificial intelligence approach |
| title | Transient security assessment for power system stability: a review on artificial intelligence approach |
| title_full | Transient security assessment for power system stability: a review on artificial intelligence approach |
| title_fullStr | Transient security assessment for power system stability: a review on artificial intelligence approach |
| title_full_unstemmed | Transient security assessment for power system stability: a review on artificial intelligence approach |
| title_short | Transient security assessment for power system stability: a review on artificial intelligence approach |
| title_sort | transient security assessment for power system stability a review on artificial intelligence approach |
| url | http://psasir.upm.edu.my/id/eprint/47756/1/Transient%20security%20assessment%20for%20power%20system%20stability%20a%20review%20on%20artificial%20intelligence%20approach.pdf |
| work_keys_str_mv | AT almasriahmednaufala transientsecurityassessmentforpowersystemstabilityareviewonartificialintelligenceapproach AT abkadirmohdzainalabidin transientsecurityassessmentforpowersystemstabilityareviewonartificialintelligenceapproach AT hizamhashim transientsecurityassessmentforpowersystemstabilityareviewonartificialintelligenceapproach AT jasnijasronita transientsecurityassessmentforpowersystemstabilityareviewonartificialintelligenceapproach AT mariunnorman transientsecurityassessmentforpowersystemstabilityareviewonartificialintelligenceapproach |