Reliability assessment of generating systems with wind power penetration via BPSO
The growing pervasiveness of the Wind Energy Conversion System (WECS) in power systems has a great influence on the electrical system reliability in relation to other conventional sources for power generation. This current study offers a binary particle swarm optimisation (BPSO) application with Wei...
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| Format: | Article |
| Language: | English |
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Indonesian Society for Knowledge and Human Development
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/27020/ http://umpir.ump.edu.my/id/eprint/27020/1/Reliability%20assessment%20of%20generating%20systems%20with%20wind%20power.pdf |
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| author | Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni Abdalla, Ahmed N. Matsukawa, Yoshiaki |
| author_facet | Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni Abdalla, Ahmed N. Matsukawa, Yoshiaki |
| author_sort | Kadhem, Athraa Ali |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The growing pervasiveness of the Wind Energy Conversion System (WECS) in power systems has a great influence on the electrical system reliability in relation to other conventional sources for power generation. This current study offers a binary particle swarm optimisation (BPSO) application with Weibull model to reliably evaluate the generation systems with a WECS. The proposed methodology is based on hourly time series wind speed and uses Weibull model and simulation of the operation of generation system, taking into consideration the random failures of conventional units of the system and the fluctuating wind energy of a WECS. The BPSO algorithm adopts intelligent research to explore the meaningful system states and accelerate their integrated convergence, so that makes it feasible to locate all possible failure states in the system states space in order to calculate the reliability indices with WECS. The numerical simulation of the suggested solution is compared with the established Monte Carlo simulation (MCS). The reliability test system (IEEE-RTS-79) is employed to show the effectiveness of the proposed algorithm. |
| first_indexed | 2025-11-15T02:45:10Z |
| format | Article |
| id | ump-27020 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:45:10Z |
| publishDate | 2017 |
| publisher | Indonesian Society for Knowledge and Human Development |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-270202020-03-23T02:59:28Z http://umpir.ump.edu.my/id/eprint/27020/ Reliability assessment of generating systems with wind power penetration via BPSO Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni Abdalla, Ahmed N. Matsukawa, Yoshiaki TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering The growing pervasiveness of the Wind Energy Conversion System (WECS) in power systems has a great influence on the electrical system reliability in relation to other conventional sources for power generation. This current study offers a binary particle swarm optimisation (BPSO) application with Weibull model to reliably evaluate the generation systems with a WECS. The proposed methodology is based on hourly time series wind speed and uses Weibull model and simulation of the operation of generation system, taking into consideration the random failures of conventional units of the system and the fluctuating wind energy of a WECS. The BPSO algorithm adopts intelligent research to explore the meaningful system states and accelerate their integrated convergence, so that makes it feasible to locate all possible failure states in the system states space in order to calculate the reliability indices with WECS. The numerical simulation of the suggested solution is compared with the established Monte Carlo simulation (MCS). The reliability test system (IEEE-RTS-79) is employed to show the effectiveness of the proposed algorithm. Indonesian Society for Knowledge and Human Development 2017 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/27020/1/Reliability%20assessment%20of%20generating%20systems%20with%20wind%20power.pdf Kadhem, Athraa Ali and Noor Izzri, Abdul Wahab and Ishak, Aris and Jasronita, Jasni and Abdalla, Ahmed N. and Matsukawa, Yoshiaki (2017) Reliability assessment of generating systems with wind power penetration via BPSO. International Journal on Advanced Science, Engineering and Information Technology, 7 (4). pp. 1248-1254. ISSN 2088-5334. (Published) https://doi.org/10.18517/ijaseit.7.4.2311 https://doi.org/10.18517/ijaseit.7.4.2311 |
| spellingShingle | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering Kadhem, Athraa Ali Noor Izzri, Abdul Wahab Ishak, Aris Jasronita, Jasni Abdalla, Ahmed N. Matsukawa, Yoshiaki Reliability assessment of generating systems with wind power penetration via BPSO |
| title | Reliability assessment of generating systems with wind power penetration via BPSO |
| title_full | Reliability assessment of generating systems with wind power penetration via BPSO |
| title_fullStr | Reliability assessment of generating systems with wind power penetration via BPSO |
| title_full_unstemmed | Reliability assessment of generating systems with wind power penetration via BPSO |
| title_short | Reliability assessment of generating systems with wind power penetration via BPSO |
| title_sort | reliability assessment of generating systems with wind power penetration via bpso |
| topic | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/27020/ http://umpir.ump.edu.my/id/eprint/27020/ http://umpir.ump.edu.my/id/eprint/27020/ http://umpir.ump.edu.my/id/eprint/27020/1/Reliability%20assessment%20of%20generating%20systems%20with%20wind%20power.pdf |