Power production optimization of model-free wind farm using simulated annealing algorithm
This research set to appraise the potency of Simulated Annealing (SA) based method within enhancement of wind farms’ power generation performance. Horns Rev Offshore Wind Farm with a total magnitude of 80 wind turbines was hereby replicated to study the recommended SA based method. Core objective of...
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my.ump.umpir.369552023-02-10T02:44:58Z http://umpir.ump.edu.my/id/eprint/36955/ Power production optimization of model-free wind farm using simulated annealing algorithm Mok, Ren Hao Mohd Ashraf, Ahmad T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering This research set to appraise the potency of Simulated Annealing (SA) based method within enhancement of wind farms’ power generation performance. Horns Rev Offshore Wind Farm with a total magnitude of 80 wind turbines was hereby replicated to study the recommended SA based method. Core objective of the simulation then focused maximization of power output through parametric fine-tuning of individual wind turbine through the SA based method. Recorded findings on boosted convergence rate, elevated accuracy and magnified power production consequentially verified efficacy of the SA based method towards operational improvement of wind farms. 2022-11-15 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/36955/1/Power%20production%20optimization%20of%20model-free%20wind%20farm%20using%20simulated%20annealing%20algorithm.pdf Mok, Ren Hao and Mohd Ashraf, Ahmad (2022) Power production optimization of model-free wind farm using simulated annealing algorithm. In: The 6th National Conference for Postgraduate Research (NCON-PGR 2022), 15 November 2022 , Virtual Conference, Universiti Malaysia Pahang, Malaysia. p. 117.. https://ncon-pgr.ump.edu.my/index.php/en/?option=com_fileman&view=file&routed=1&name=E-BOOK%20NCON%202022%20.pdf&folder=E-BOOK%20NCON%202022&container=fileman-files |
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T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Mok, Ren Hao Mohd Ashraf, Ahmad Power production optimization of model-free wind farm using simulated annealing algorithm |
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This research set to appraise the potency of Simulated Annealing (SA) based method within enhancement of wind farms’ power generation performance. Horns Rev Offshore Wind Farm with a total magnitude of 80 wind turbines was hereby replicated to study the recommended SA based method. Core objective of the simulation then focused maximization of power output through parametric fine-tuning of individual wind turbine through the SA based method. Recorded findings on boosted convergence rate, elevated accuracy and magnified power production consequentially verified efficacy of the SA based method towards operational improvement of wind farms. |
format |
Conference or Workshop Item |
author |
Mok, Ren Hao Mohd Ashraf, Ahmad |
author_facet |
Mok, Ren Hao Mohd Ashraf, Ahmad |
author_sort |
Mok, Ren Hao |
title |
Power production optimization of model-free wind farm using simulated annealing algorithm |
title_short |
Power production optimization of model-free wind farm using simulated annealing algorithm |
title_full |
Power production optimization of model-free wind farm using simulated annealing algorithm |
title_fullStr |
Power production optimization of model-free wind farm using simulated annealing algorithm |
title_full_unstemmed |
Power production optimization of model-free wind farm using simulated annealing algorithm |
title_sort |
power production optimization of model-free wind farm using simulated annealing algorithm |
publishDate |
2022 |
url |
http://umpir.ump.edu.my/id/eprint/36955/1/Power%20production%20optimization%20of%20model-free%20wind%20farm%20using%20simulated%20annealing%20algorithm.pdf http://umpir.ump.edu.my/id/eprint/36955/ https://ncon-pgr.ump.edu.my/index.php/en/?option=com_fileman&view=file&routed=1&name=E-BOOK%20NCON%202022%20.pdf&folder=E-BOOK%20NCON%202022&container=fileman-files |
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13.211869 |