Reliability assessment of power generation systems using intelligent search based on disparity theory
The reliability of the generating system adequacy is evaluated based on the ability of the system to satisfy the load demand. In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. Disparity evo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/62948/ http://psasir.upm.edu.my/id/eprint/62948/1/Reliability%20Assessment%20of%20Power%20Generation%20Systems%20Using%20Intelligent%20Search%20Based%20on%20Disparity%20Theory.pdf |
| _version_ | 1848854696203124736 |
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| author | Kadhem, Athraa Ali Abdul Wahab, Noor Izzri Aris, Ishak Jasni, Jasronita Abdalla, Ahmed N. |
| author_facet | Kadhem, Athraa Ali Abdul Wahab, Noor Izzri Aris, Ishak Jasni, Jasronita Abdalla, Ahmed N. |
| author_sort | Kadhem, Athraa Ali |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The reliability of the generating system adequacy is evaluated based on the ability of the system to satisfy the load demand. In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. The DEGA is based on metaheuristic searching for the truncated sampling of state-space for the reliability assessment of power generation system adequacy. Two reliability test systems (IEEE-RTS-79 and (IEEE-RTS-96) are used to demonstrate the effectiveness of the proposed algorithm. The simulation result shows the DEGA can generate a larger variety of the individuals in an early stage of the next population generation. It is also able to estimate the reliability indices accurately. |
| first_indexed | 2025-11-15T11:13:58Z |
| format | Article |
| id | upm-62948 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:13:58Z |
| publishDate | 2017 |
| publisher | MDPI |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-629482018-09-28T10:45:34Z http://psasir.upm.edu.my/id/eprint/62948/ Reliability assessment of power generation systems using intelligent search based on disparity theory Kadhem, Athraa Ali Abdul Wahab, Noor Izzri Aris, Ishak Jasni, Jasronita Abdalla, Ahmed N. The reliability of the generating system adequacy is evaluated based on the ability of the system to satisfy the load demand. In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. The DEGA is based on metaheuristic searching for the truncated sampling of state-space for the reliability assessment of power generation system adequacy. Two reliability test systems (IEEE-RTS-79 and (IEEE-RTS-96) are used to demonstrate the effectiveness of the proposed algorithm. The simulation result shows the DEGA can generate a larger variety of the individuals in an early stage of the next population generation. It is also able to estimate the reliability indices accurately. MDPI 2017-03-10 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/62948/1/Reliability%20Assessment%20of%20Power%20Generation%20Systems%20Using%20Intelligent%20Search%20Based%20on%20Disparity%20Theory.pdf Kadhem, Athraa Ali and Abdul Wahab, Noor Izzri and Aris, Ishak and Jasni, Jasronita and Abdalla, Ahmed N. (2017) Reliability assessment of power generation systems using intelligent search based on disparity theory. Energies, 10 (343). pp. 1-13. ISSN 1996-1073 http://www.mdpi.com/1996-1073/10/3/343/htm 10.3390/en10030343 |
| spellingShingle | Kadhem, Athraa Ali Abdul Wahab, Noor Izzri Aris, Ishak Jasni, Jasronita Abdalla, Ahmed N. Reliability assessment of power generation systems using intelligent search based on disparity theory |
| title | Reliability assessment of power generation systems using intelligent search based on disparity theory |
| title_full | Reliability assessment of power generation systems using intelligent search based on disparity theory |
| title_fullStr | Reliability assessment of power generation systems using intelligent search based on disparity theory |
| title_full_unstemmed | Reliability assessment of power generation systems using intelligent search based on disparity theory |
| title_short | Reliability assessment of power generation systems using intelligent search based on disparity theory |
| title_sort | reliability assessment of power generation systems using intelligent search based on disparity theory |
| url | http://psasir.upm.edu.my/id/eprint/62948/ http://psasir.upm.edu.my/id/eprint/62948/ http://psasir.upm.edu.my/id/eprint/62948/ http://psasir.upm.edu.my/id/eprint/62948/1/Reliability%20Assessment%20of%20Power%20Generation%20Systems%20Using%20Intelligent%20Search%20Based%20on%20Disparity%20Theory.pdf |