Harris hawks optimization algorithm for model order reduction of interconnected wind turbines

Roy, Ranadip; Mukherjee, V.; Singh, Rudra Pratap

doi:10.1016/j.isatra.2021.09.019

Cited by 16 publications

(7 citation statements)

References 39 publications

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“…The HHO algorithm consists of three stages, that is, (i) exploration, (ii) transform exploration to exploitation, and (iii) exploitation. 46,48,53 Exploration. The characteristic of sharp in detecting prey using the roving eyes of Harris hawks is utilized here for parameters optimization of our proposed ASIERL-ISMC.…”

Section: Harris Hawks Optimizationmentioning

confidence: 99%

Harris hawks optimization tuned exponential reaching law based integral SMC for pitch control of linear hydraulic actuated wind turbines

Venkaiah,

Sarkar,

Chatterjee

2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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In the present study 5MW NREL horizontal axis wind turbine (HAWT) has been considered for pitch control to reduce fatigue loads and maintain rated power in region III of operation, that is, above rated wind condition. An electrohydraulic linear actuation system has been considered for blade-pitch revolve-motion of the rotor blade, based upon available wind speed. An augmented state improved exponential reaching law integral sliding mode controller (ASIERL-ISMC) has been designed for the HAWT pitch control application. In contrast to the previously reported improved exponential reaching law based controllers, in our ASIERL-ISMC, all state variables and the sliding variable have been considered together to define an augmented reaching law that can enhance the degree of freedom of the controller. Further, hyperparameters of the proposed ASIERL-ISMC have been optimized using Harris hawks optimization (HHO), to achieve superior control performance. The performances of this proposed HHO-ASIERL-ISMC have been compared with existing dynamic exponential term reaching law integral sliding mode controller (DETRL-ISMC) and improved exponential reaching law integral sliding mode controller (IERL-ISMC). The robustness and sensitivity of the proposed ASIERL-ISMC and HHO-ASIERL-ISMC have also been tested with three different available wind data. The proposed HHO-ASIERL-ISMC has been found to provide the most superior performance, in terms of both blade-pitch angle error (computed using integral absolute error (IAE)) and control energy (CE).

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Section: Harris Hawks Optimizationmentioning

confidence: 99%

Harris hawks optimization tuned exponential reaching law based integral SMC for pitch control of linear hydraulic actuated wind turbines

Venkaiah,

Sarkar,

Chatterjee

2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…Roy et al [229] used the HHO to reduce the interconnected wind turbines. They compared it with PSO, FPA, GWO, MVO, WOA, MFO, and BOA.…”

Section: Wind Applicationsmentioning

confidence: 99%

Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications

et al. 2022

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The Harris hawk optimizer is a recent population-based metaheuristics algorithm that simulates the hunting behavior of hawks. This swarm-based optimizer performs the optimization procedure using a novel way of exploration and exploitation and the multiphases of search. In this review research, we focused on the applications and developments of the recent well-established robust optimizer Harris hawk optimizer (HHO) as one of the most popular swarm-based techniques of 2020. Moreover, several experiments were carried out to prove the powerfulness and effectivness of HHO compared with nine other state-of-art algorithms using Congress on Evolutionary Computation (CEC2005) and CEC2017. The literature review paper includes deep insight about possible future directions and possible ideas worth investigations regarding the new variants of the HHO algorithm and its widespread applications.

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“…Roy et al. [ 19 ] applied HHO to integrated a more effectiveness and robustness model order reduction.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Improved Greedy Harris Hawks Optimizer and Its Application to Feature Selection

Zou

Zhou

2022

Entropy

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To overcome the lack of flexibility of Harris Hawks Optimization (HHO) in switching between exploration and exploitation, and the low efficiency of its exploitation phase, an efficient improved greedy Harris Hawks Optimizer (IGHHO) is proposed and applied to the feature selection (FS) problem. IGHHO uses a new transformation strategy that enables flexible switching between search and development, enabling it to jump out of local optima. We replace the original HHO exploitation process with improved differential perturbation and a greedy strategy to improve its global search capability. We tested it in experiments against seven algorithms using single-peaked, multi-peaked, hybrid, and composite CEC2017 benchmark functions, and IGHHO outperformed them on optimization problems with different feature functions. We propose new objective functions for the problem of data imbalance in FS and apply IGHHO to it. IGHHO outperformed comparison algorithms in terms of classification accuracy and feature subset length. The results show that IGHHO applies not only to global optimization of different feature functions but also to practical optimization problems.

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Harris hawks optimization algorithm for model order reduction of interconnected wind turbines

Cited by 16 publications

References 39 publications

Harris hawks optimization tuned exponential reaching law based integral SMC for pitch control of linear hydraulic actuated wind turbines

Harris hawks optimization tuned exponential reaching law based integral SMC for pitch control of linear hydraulic actuated wind turbines

Recent Advances in Harris Hawks Optimization: A Comparative Study and Applications

An Efficient Improved Greedy Harris Hawks Optimizer and Its Application to Feature Selection

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