Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm
<p dir="ltr">The present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. The traditional LCA (t‐LCA) inspires from the conduct of liver tumours and integrates biological ethics during the optimizati...
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2024
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| _version_ | 1864513540063232000 |
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| author | Noor Habib Khan (22224775) |
| author2 | Yong Wang (12837) Salman Habib (16524330) Raheela Jamal (22224778) Muhammad Majid Gulzar (22224781) S. M. Muyeen (14778337) Mohamed Ebeed (13991247) |
| author2_role | author author author author author author |
| author_facet | Noor Habib Khan (22224775) Yong Wang (12837) Salman Habib (16524330) Raheela Jamal (22224778) Muhammad Majid Gulzar (22224781) S. M. Muyeen (14778337) Mohamed Ebeed (13991247) |
| author_role | author |
| dc.creator.none.fl_str_mv | Noor Habib Khan (22224775) Yong Wang (12837) Salman Habib (16524330) Raheela Jamal (22224778) Muhammad Majid Gulzar (22224781) S. M. Muyeen (14778337) Mohamed Ebeed (13991247) |
| dc.date.none.fl_str_mv | 2024-10-15T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1049/rpg2.13113 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Stochastic_optimal_power_flow_framework_with_incorporation_of_wind_turbines_and_solar_PVs_using_improved_liver_cancer_algorithm/30094636 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electrical engineering Electronics, sensors and digital hardware Benchmark functions statistical validation Stochastic optimal power flow Stagnation and local optima |
| dc.title.none.fl_str_mv | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. The traditional LCA (t‐LCA) inspires from the conduct of liver tumours and integrates biological ethics during the optimization procedure. However, t‐LCA facing stagnation issues and may trap into local optima. To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. Moreover, ILCA is applied to resolve the stochastic renewable‐based (wind turbines + PVs) optimal power flow problem using a modified RER‐based IEEE 57‐bus. The objective of this work is to obtain the minimum predicted power losses and enhance the predicted voltage stability. By incorporation of renewable resources into the modified IEEE57‐bus network can help the system to reduce the power losses from 5.6622 to 3.8142 MW, while the voltage stability is enhanced from 0.1700 to 0.1164 p.u.</p><h2>Other Information</h2><p dir="ltr">Published in: IET Renewable Power Generation<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1049/rpg2.13113" target="_blank">https://dx.doi.org/10.1049/rpg2.13113</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_e61e9a4e03869c3016ba2b512509c25f |
| identifier_str_mv | 10.1049/rpg2.13113 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30094636 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithmNoor Habib Khan (22224775)Yong Wang (12837)Salman Habib (16524330)Raheela Jamal (22224778)Muhammad Majid Gulzar (22224781)S. M. Muyeen (14778337)Mohamed Ebeed (13991247)EngineeringElectrical engineeringElectronics, sensors and digital hardwareBenchmark functionsstatistical validationStochastic optimal power flowStagnation and local optima<p dir="ltr">The present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. The traditional LCA (t‐LCA) inspires from the conduct of liver tumours and integrates biological ethics during the optimization procedure. However, t‐LCA facing stagnation issues and may trap into local optima. To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. Moreover, ILCA is applied to resolve the stochastic renewable‐based (wind turbines + PVs) optimal power flow problem using a modified RER‐based IEEE 57‐bus. The objective of this work is to obtain the minimum predicted power losses and enhance the predicted voltage stability. By incorporation of renewable resources into the modified IEEE57‐bus network can help the system to reduce the power losses from 5.6622 to 3.8142 MW, while the voltage stability is enhanced from 0.1700 to 0.1164 p.u.</p><h2>Other Information</h2><p dir="ltr">Published in: IET Renewable Power Generation<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1049/rpg2.13113" target="_blank">https://dx.doi.org/10.1049/rpg2.13113</a></p>2024-10-15T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1049/rpg2.13113https://figshare.com/articles/journal_contribution/Stochastic_optimal_power_flow_framework_with_incorporation_of_wind_turbines_and_solar_PVs_using_improved_liver_cancer_algorithm/30094636CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/300946362024-10-15T09:00:00Z |
| spellingShingle | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm Noor Habib Khan (22224775) Engineering Electrical engineering Electronics, sensors and digital hardware Benchmark functions statistical validation Stochastic optimal power flow Stagnation and local optima |
| status_str | publishedVersion |
| title | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm |
| title_full | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm |
| title_fullStr | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm |
| title_full_unstemmed | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm |
| title_short | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm |
| title_sort | Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm |
| topic | Engineering Electrical engineering Electronics, sensors and digital hardware Benchmark functions statistical validation Stochastic optimal power flow Stagnation and local optima |