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 AG
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/20435/ http://umpir.ump.edu.my/id/eprint/20435/1/Reliability%20assessment%20of%20power%20generation%20systems%20using%20intelligent%20search%20based%20on%20disparity%20theory.pdf |
| _version_ | 1848821100417384448 |
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| author | Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni Abdalla, Ahmed N. |
| author_facet | Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni Abdalla, Ahmed N. |
| author_sort | Kadhem, Athraa Ali |
| building | UMP 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 | 2025-11-15T02:19:59Z |
| format | Article |
| id | ump-20435 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:19:59Z |
| publishDate | 2017 |
| publisher | MDPI AG |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-204352018-10-03T07:29:08Z http://umpir.ump.edu.my/id/eprint/20435/ Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni Abdalla, Ahmed N. T Technology (General) 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 AG 2017 Article PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/20435/1/Reliability%20assessment%20of%20power%20generation%20systems%20using%20intelligent%20search%20based%20on%20disparity%20theory.pdf Kadhem, Athraa Ali and Noor Izzri, Abdul Wahab and Ishak, Aris and Jasronita, Jasni and Abdalla, Ahmed N. (2017) Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory. Energies, 10 (3). pp. 1-13. ISSN 1996-1073 . (Published) http://dx.doi.org/10.3390/en10030343 doi: 10.3390/en10030343 |
| spellingShingle | T Technology (General) Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni 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 |
| topic | T Technology (General) |
| url | http://umpir.ump.edu.my/id/eprint/20435/ http://umpir.ump.edu.my/id/eprint/20435/ http://umpir.ump.edu.my/id/eprint/20435/ http://umpir.ump.edu.my/id/eprint/20435/1/Reliability%20assessment%20of%20power%20generation%20systems%20using%20intelligent%20search%20based%20on%20disparity%20theory.pdf |