Model-free wind farm control based on random search
This paper explores a model-free approach based on the random search (RS) algorithm for maximizing wind farms power production. The RS based approach is utilized to find the optimal control parameter of each turbine in maximizing the wind farm total power production. The Horns Rev wind farm model wi...
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Online Access: | http://umpir.ump.edu.my/id/eprint/18239/ http://umpir.ump.edu.my/id/eprint/18239/ http://umpir.ump.edu.my/id/eprint/18239/1/Model-free%20Wind%20Farm%20Control%20Based%20on%20Random%20Search.pdf http://umpir.ump.edu.my/id/eprint/18239/7/Model-free%20Wind%20Farm%20Control%20Based%20on%20Random%20Search%201.pdf |
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ump-182392018-07-19T03:27:25Z http://umpir.ump.edu.my/id/eprint/18239/ Model-free wind farm control based on random search Mohd Ashraf, Ahmad Hao, Mok Ren Raja Mohd Taufika, Raja Ismail Ahmad Nor Kasruddin, Nasir TK Electrical engineering. Electronics Nuclear engineering This paper explores a model-free approach based on the random search (RS) algorithm for maximizing wind farms power production. The RS based approach is utilized to find the optimal control parameter of each turbine in maximizing the wind farm total power production. The Horns Rev wind farm model with turbulence interaction between turbines is used to validate the proposed approach. Simulation results demonstrate that the random search approach produces higher total power production as compared to the existing method. IEEE 2017-03 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/18239/1/Model-free%20Wind%20Farm%20Control%20Based%20on%20Random%20Search.pdf pdf en http://umpir.ump.edu.my/id/eprint/18239/7/Model-free%20Wind%20Farm%20Control%20Based%20on%20Random%20Search%201.pdf Mohd Ashraf, Ahmad and Hao, Mok Ren and Raja Mohd Taufika, Raja Ismail and Ahmad Nor Kasruddin, Nasir (2017) Model-free wind farm control based on random search. In: IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS 2016), 22 October 2016 , UniversIti Teknologi Mara Shah Alam, Malaysia. pp. 131-134.. ISBN 978-1-5090-4186-2 https://ieeexplore.ieee.org/document/7885302/ |
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TK Electrical engineering. Electronics Nuclear engineering |
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TK Electrical engineering. Electronics Nuclear engineering Mohd Ashraf, Ahmad Hao, Mok Ren Raja Mohd Taufika, Raja Ismail Ahmad Nor Kasruddin, Nasir Model-free wind farm control based on random search |
description |
This paper explores a model-free approach based on the random search (RS) algorithm for maximizing wind farms power production. The RS based approach is utilized to find the optimal control parameter of each turbine in maximizing the wind farm total power production. The Horns Rev wind farm model with turbulence interaction between turbines is used to validate the proposed approach. Simulation results demonstrate that the random search approach produces higher total power production as compared to the existing method. |
format |
Conference or Workshop Item |
author |
Mohd Ashraf, Ahmad Hao, Mok Ren Raja Mohd Taufika, Raja Ismail Ahmad Nor Kasruddin, Nasir |
author_facet |
Mohd Ashraf, Ahmad Hao, Mok Ren Raja Mohd Taufika, Raja Ismail Ahmad Nor Kasruddin, Nasir |
author_sort |
Mohd Ashraf, Ahmad |
title |
Model-free wind farm control based on random search |
title_short |
Model-free wind farm control based on random search |
title_full |
Model-free wind farm control based on random search |
title_fullStr |
Model-free wind farm control based on random search |
title_full_unstemmed |
Model-free wind farm control based on random search |
title_sort |
model-free wind farm control based on random search |
publisher |
IEEE |
publishDate |
2017 |
url |
http://umpir.ump.edu.my/id/eprint/18239/ http://umpir.ump.edu.my/id/eprint/18239/ http://umpir.ump.edu.my/id/eprint/18239/1/Model-free%20Wind%20Farm%20Control%20Based%20on%20Random%20Search.pdf http://umpir.ump.edu.my/id/eprint/18239/7/Model-free%20Wind%20Farm%20Control%20Based%20on%20Random%20Search%201.pdf |
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2023-09-18T22:25:44Z |
last_indexed |
2023-09-18T22:25:44Z |
_version_ |
1777415953224564736 |