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Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system

This paper presents a novel heuristic based recurrent Hopfield neural network (HNN) designed self-adaptive proportional-integral-derivative (PID) controller for automatic load frequency control of interconnected hybrid power system (HPS). The control problem is conceptualized as an optimization prob...

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Main Authors: Veerasamy, Veerapandiyan, Abdul Wahab, Noor Izzri, Ramachandran, Rajeswari, Othman, Mohammad Lutfi, Hizam, Hashim, Kumar, Jeevitha Satheesh, Irudayaraj, Andrew Xavier Raj
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Published: Elsevier 2022
Online Access:http://psasir.upm.edu.my/id/eprint/100908/
https://www.sciencedirect.com/science/article/pii/S0957417421016912
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spelling my.upm.eprints.1009082023-07-14T08:32:34Z http://psasir.upm.edu.my/id/eprint/100908/ Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system Veerasamy, Veerapandiyan Abdul Wahab, Noor Izzri Ramachandran, Rajeswari Othman, Mohammad Lutfi Hizam, Hashim Kumar, Jeevitha Satheesh Irudayaraj, Andrew Xavier Raj This paper presents a novel heuristic based recurrent Hopfield neural network (HNN) designed self-adaptive proportional-integral-derivative (PID) controller for automatic load frequency control of interconnected hybrid power system (HPS). The control problem is conceptualized as an optimization problem and solved using a heuristic optimization technique with the aim of minimizing the Lyapunov function. Initially, the energy function is formulated and the differential equations governing the dynamics of HNN are derived. Then, these dynamics are solved using hybrid particle swarm optimization-gravitational search algorithm (PSO-GSA) to obtain the initial solution. The effectiveness of the controller is tested for two-area system considering the system non-linearities and integration of plug-in-electric vehicle (PEV). Further, to improve the speed of response of the system, the cascade control scheme is proposed using the presented approach of heuristic based HNN (h-HNN). The efficacy of the method is examined in single- and multi-loop PID control of three-area HPS. The performance of propounded control schemes is compared with PSO-GSA and generalized HNN based PID controller. The results obtained show that the response of proposed controller is superior in terms of transient and steady state performance indices measured. In addition, the control effort of suggested cascade controller is much reduced compared with other controllers presented. Furthermore, the self-adaptive property of the controller is analyzed for random change in load demand and their corresponding change in gain parameters are recorded. This reveals that the proposed controller is more suitable for stable operation of modern power network with green energy technologies and PEV efficiently. Elsevier 2022-04-15 Article PeerReviewed Veerasamy, Veerapandiyan and Abdul Wahab, Noor Izzri and Ramachandran, Rajeswari and Othman, Mohammad Lutfi and Hizam, Hashim and Kumar, Jeevitha Satheesh and Irudayaraj, Andrew Xavier Raj (2022) Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system. Expert Systems with Applications, 192. art. no. 116402. pp. 1-17. ISSN 0957-4174 https://www.sciencedirect.com/science/article/pii/S0957417421016912 10.1016/j.eswa.2021.116402
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description This paper presents a novel heuristic based recurrent Hopfield neural network (HNN) designed self-adaptive proportional-integral-derivative (PID) controller for automatic load frequency control of interconnected hybrid power system (HPS). The control problem is conceptualized as an optimization problem and solved using a heuristic optimization technique with the aim of minimizing the Lyapunov function. Initially, the energy function is formulated and the differential equations governing the dynamics of HNN are derived. Then, these dynamics are solved using hybrid particle swarm optimization-gravitational search algorithm (PSO-GSA) to obtain the initial solution. The effectiveness of the controller is tested for two-area system considering the system non-linearities and integration of plug-in-electric vehicle (PEV). Further, to improve the speed of response of the system, the cascade control scheme is proposed using the presented approach of heuristic based HNN (h-HNN). The efficacy of the method is examined in single- and multi-loop PID control of three-area HPS. The performance of propounded control schemes is compared with PSO-GSA and generalized HNN based PID controller. The results obtained show that the response of proposed controller is superior in terms of transient and steady state performance indices measured. In addition, the control effort of suggested cascade controller is much reduced compared with other controllers presented. Furthermore, the self-adaptive property of the controller is analyzed for random change in load demand and their corresponding change in gain parameters are recorded. This reveals that the proposed controller is more suitable for stable operation of modern power network with green energy technologies and PEV efficiently.
format Article
author Veerasamy, Veerapandiyan
Abdul Wahab, Noor Izzri
Ramachandran, Rajeswari
Othman, Mohammad Lutfi
Hizam, Hashim
Kumar, Jeevitha Satheesh
Irudayaraj, Andrew Xavier Raj
spellingShingle Veerasamy, Veerapandiyan
Abdul Wahab, Noor Izzri
Ramachandran, Rajeswari
Othman, Mohammad Lutfi
Hizam, Hashim
Kumar, Jeevitha Satheesh
Irudayaraj, Andrew Xavier Raj
Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system
author_facet Veerasamy, Veerapandiyan
Abdul Wahab, Noor Izzri
Ramachandran, Rajeswari
Othman, Mohammad Lutfi
Hizam, Hashim
Kumar, Jeevitha Satheesh
Irudayaraj, Andrew Xavier Raj
author_sort Veerasamy, Veerapandiyan
title Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system
title_short Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system
title_full Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system
title_fullStr Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system
title_full_unstemmed Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system
title_sort design of single- and multi-loop self-adaptive pid controller using heuristic based recurrent neural network for alfc of hybrid power system
publisher Elsevier
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/100908/
https://www.sciencedirect.com/science/article/pii/S0957417421016912
_version_ 1772813408082591744
score 13.211869

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