Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant

The main challenge in controlling the wind plant nowadays is a highly arduous effort in discovering the best controller parameters of the turbines due to the wake interaction effect. The aim of this paper is to develop the data-driven control based on marine predators algorithm (MPA) for fine-tuning...

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Main Authors: Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/36154/
http://umpir.ump.edu.my/id/eprint/36154/1/Data-driven_control_based_on_marine_predators_algorithm_for_optimal_tuning_of_the_wind_plant.pdf
http://umpir.ump.edu.my/id/eprint/36154/7/Data-driven%20control%20based%20on%20marine%20predators%20algorithm%20for%20optimal%20tuning%20.pdf
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author Mohd Zaidi, Mohd Tumari
Mohd Ashraf, Ahmad
Mohd Helmi, Suid
Mohd Riduwan, Ghazali
author_facet Mohd Zaidi, Mohd Tumari
Mohd Ashraf, Ahmad
Mohd Helmi, Suid
Mohd Riduwan, Ghazali
author_sort Mohd Zaidi, Mohd Tumari
building UMP Institutional Repository
collection Online Access
description The main challenge in controlling the wind plant nowadays is a highly arduous effort in discovering the best controller parameters of the turbines due to the wake interaction effect. The aim of this paper is to develop the data-driven control based on marine predators algorithm (MPA) for fine-tuning the controller parameters of a single row of ten turbines in improving the wind plant power production according to the reference power. The real wind plant model from Denmark named Horns Rev is considered in this study. Effectiveness of the proposed method was particularly assessed according to the convergence curve and statistical analysis of the fitness function, and Wilcoxon's rank test. Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.
first_indexed 2025-11-15T03:20:57Z
format Conference or Workshop Item
id ump-36154
institution Universiti Malaysia Pahang
institution_category Local University
language English
English
last_indexed 2025-11-15T03:20:57Z
publishDate 2022
publisher Institute of Electrical and Electronics Engineers Inc.
recordtype eprints
repository_type Digital Repository
spelling ump-361542023-10-31T02:52:28Z http://umpir.ump.edu.my/id/eprint/36154/ Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant Mohd Zaidi, Mohd Tumari Mohd Ashraf, Ahmad Mohd Helmi, Suid Mohd Riduwan, Ghazali TK Electrical engineering. Electronics Nuclear engineering The main challenge in controlling the wind plant nowadays is a highly arduous effort in discovering the best controller parameters of the turbines due to the wake interaction effect. The aim of this paper is to develop the data-driven control based on marine predators algorithm (MPA) for fine-tuning the controller parameters of a single row of ten turbines in improving the wind plant power production according to the reference power. The real wind plant model from Denmark named Horns Rev is considered in this study. Effectiveness of the proposed method was particularly assessed according to the convergence curve and statistical analysis of the fitness function, and Wilcoxon's rank test. Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm. Institute of Electrical and Electronics Engineers Inc. 2022-12-26 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/36154/1/Data-driven_control_based_on_marine_predators_algorithm_for_optimal_tuning_of_the_wind_plant.pdf pdf en http://umpir.ump.edu.my/id/eprint/36154/7/Data-driven%20control%20based%20on%20marine%20predators%20algorithm%20for%20optimal%20tuning%20.pdf Mohd Zaidi, Mohd Tumari and Mohd Ashraf, Ahmad and Mohd Helmi, Suid and Mohd Riduwan, Ghazali (2022) Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant. In: 2022 IEEE International Conference on Power and Energy: Advancement in Power and Energy Systems towards Sustainable and Resilient Energy Supply, PECon 2022Pages 203 - 2082022; 9th IEEE International Conference on Power and Energy, PECon 2022 , 5 - 6 December 2022 , Langkawi, Kedah. pp. 203-208.. ISBN 978-166540990-2 (Published) https://doi.org/ 10.1109/PECon54459.2022.9988895
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd Zaidi, Mohd Tumari
Mohd Ashraf, Ahmad
Mohd Helmi, Suid
Mohd Riduwan, Ghazali
Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
title Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
title_full Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
title_fullStr Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
title_full_unstemmed Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
title_short Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
title_sort data-driven control based on marine predators algorithm for optimal tuning of the wind plant
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/36154/
http://umpir.ump.edu.my/id/eprint/36154/
http://umpir.ump.edu.my/id/eprint/36154/1/Data-driven_control_based_on_marine_predators_algorithm_for_optimal_tuning_of_the_wind_plant.pdf
http://umpir.ump.edu.my/id/eprint/36154/7/Data-driven%20control%20based%20on%20marine%20predators%20algorithm%20for%20optimal%20tuning%20.pdf