A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants

This paper introduces a novel metaheuristic approach of sooty terns optimization algorithm (STOA) to determine the optimum parameters of model predictive control (MPC)-based deregulated load frequency control (LFC). The system structure consists of three interconnected plants with nonlinear multisou...

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Main Authors: Hossam Hassan Ali, Ahmed Fathy, Abdullah M. Al-Shaalan, Ahmed M. Kassem, Hassan M. H. Farh, Abdullrahman A. Al-Shamma’a, Hossam A. Gabbar
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/17/5393
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author Hossam Hassan Ali
Ahmed Fathy
Abdullah M. Al-Shaalan
Ahmed M. Kassem
Hassan M. H. Farh
Abdullrahman A. Al-Shamma’a
Hossam A. Gabbar
author_facet Hossam Hassan Ali
Ahmed Fathy
Abdullah M. Al-Shaalan
Ahmed M. Kassem
Hassan M. H. Farh
Abdullrahman A. Al-Shamma’a
Hossam A. Gabbar
author_sort Hossam Hassan Ali
collection DOAJ
description This paper introduces a novel metaheuristic approach of sooty terns optimization algorithm (STOA) to determine the optimum parameters of model predictive control (MPC)-based deregulated load frequency control (LFC). The system structure consists of three interconnected plants with nonlinear multisources comprising wind turbine, photovoltaic model with maximum power point tracker, and superconducting magnetic energy storage under deregulated environment. The proposed objective function is the integral time absolute error (ITAE) of the deviations in frequencies and powers in tie-lines. The analysis aims at determining the optimum parameters of MPC via STOA such that ITAE is minimized. Moreover, the proposed STOA-MPC is examined under variation of the system parameters and random load disturbance. The time responses and performance specifications of the proposed STOA-MPC are compared to those obtained with MPC optimized via differential evolution, intelligent water drops algorithm, stain bower braid algorithm, and firefly algorithm. Furthermore, a practical case study of interconnected system comprising the Kuraymat solar thermal power station is analyzed based on actual recorded solar radiation. The obtained results via the proposed STOA-MPC-based deregulated LFC confirmed the competence and robustness of the designed controller compared to the other algorithms.
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spelling doaj.art-72e5b265853049d28192dc864ebd25602023-11-22T10:34:07ZengMDPI AGEnergies1996-10732021-08-011417539310.3390/en14175393A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy PlantsHossam Hassan Ali0Ahmed Fathy1Abdullah M. Al-Shaalan2Ahmed M. Kassem3Hassan M. H. Farh4Abdullrahman A. Al-Shamma’a5Hossam A. Gabbar6Electrical Department, Faculty of Technology and Education, Sohag University, Sohag 82524, EgyptElectrical Power & Machine Department, Faculty of Engineering, Zagazig University, Zagazig 44519, EgyptElectrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi ArabiaElectrical Engineering Department, Faculty of Engineering, Sohag University, Sohag 82524, EgyptElectrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi ArabiaElectrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi ArabiaFaculty of Energy Systems and Nuclear Science, Ontario Tech University (UOIT), 2000 Simcoe St N, Oshawa, ON L1G 0C5, CanadaThis paper introduces a novel metaheuristic approach of sooty terns optimization algorithm (STOA) to determine the optimum parameters of model predictive control (MPC)-based deregulated load frequency control (LFC). The system structure consists of three interconnected plants with nonlinear multisources comprising wind turbine, photovoltaic model with maximum power point tracker, and superconducting magnetic energy storage under deregulated environment. The proposed objective function is the integral time absolute error (ITAE) of the deviations in frequencies and powers in tie-lines. The analysis aims at determining the optimum parameters of MPC via STOA such that ITAE is minimized. Moreover, the proposed STOA-MPC is examined under variation of the system parameters and random load disturbance. The time responses and performance specifications of the proposed STOA-MPC are compared to those obtained with MPC optimized via differential evolution, intelligent water drops algorithm, stain bower braid algorithm, and firefly algorithm. Furthermore, a practical case study of interconnected system comprising the Kuraymat solar thermal power station is analyzed based on actual recorded solar radiation. The obtained results via the proposed STOA-MPC-based deregulated LFC confirmed the competence and robustness of the designed controller compared to the other algorithms.https://www.mdpi.com/1996-1073/14/17/5393deregulated LFCrenewable energymodel predictive controlsooty terns optimization
spellingShingle Hossam Hassan Ali
Ahmed Fathy
Abdullah M. Al-Shaalan
Ahmed M. Kassem
Hassan M. H. Farh
Abdullrahman A. Al-Shamma’a
Hossam A. Gabbar
A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants
Energies
deregulated LFC
renewable energy
model predictive control
sooty terns optimization
title A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants
title_full A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants
title_fullStr A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants
title_full_unstemmed A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants
title_short A Novel Sooty Terns Algorithm for Deregulated MPC-LFC Installed in Multi-Interconnected System with Renewable Energy Plants
title_sort novel sooty terns algorithm for deregulated mpc lfc installed in multi interconnected system with renewable energy plants
topic deregulated LFC
renewable energy
model predictive control
sooty terns optimization
url https://www.mdpi.com/1996-1073/14/17/5393
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