SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer

Abstract The current study uses the Chernobyl disaster optimizer (CDO), a new metaheuristic optimizer, to identify the seven unknown parameters of solid oxide fuel cells (SOFCs). The procedures of the CDO is based on physical behavior of the elaborated radiations from the well-known Chernobyl disast...

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Main Authors: Sameh I. Selem, Attia A. El-Fergany, Eid A. Gouda, Mohamed F. Kotb, Islam Ismael
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-86493-y
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author Sameh I. Selem
Attia A. El-Fergany
Eid A. Gouda
Mohamed F. Kotb
Islam Ismael
author_facet Sameh I. Selem
Attia A. El-Fergany
Eid A. Gouda
Mohamed F. Kotb
Islam Ismael
author_sort Sameh I. Selem
collection DOAJ
description Abstract The current study uses the Chernobyl disaster optimizer (CDO), a new metaheuristic optimizer, to identify the seven unknown parameters of solid oxide fuel cells (SOFCs). The procedures of the CDO is based on physical behavior of the elaborated radiations from the well-known Chernobyl disaster according to their mass, speed, frequency, and degree of ionization. The sum of square errors (SMSE) among the estimated and the real measured output voltage datasets of SOFCs is minimized employing the CDO. Set of boundaries of the SOFC’s process is taken into consideration with the problem formulation. SOFCs stack’s model is examined at 800οC and 900οC and its performance is confirmed. The CDO extracts more precise SOFCs’ parameters compared to other competitors. The CDO’s convergence patterns and the SOFCs unit’s performance are studied and proved at steady-state by comparing its results to a number of recognized algorithms under varied operating scenarios. A significant SMSE’s values of 3.46 µV2 and 7.38 µV2 are attained at 800οC and 900οC, respectively by the CDO. As a result, the polarization principal curves of the measured and estimated voltage datasets are checked and verified with very close matching. The dynamic behavior of the SOFCs stack is examined in relation to direct load, electric networks, and superconducting magnetic energy storage devices (SMES) for additional validation and illustration. The role of the SOFCs stack in controlling the active and reactive power delivered to the network and direct load is investigated using two controllers: one to control the inverter, which converts the SOFC’s dc output to the main network, and the other to control the SMES. The Simulink/MATLAB environment is used to indicate the validity of the proposed framework under both steady-state and dynamical conditions. The comprehensive assessments show that the CDO capabilities are very effective when used with microgrids.
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spelling doaj-art-9a11c5a92e43400ab3ccad727ccb12112025-01-26T12:25:53ZengNature PortfolioScientific Reports2045-23222025-01-0115111710.1038/s41598-025-86493-ySOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizerSameh I. Selem0Attia A. El-Fergany1Eid A. Gouda2Mohamed F. Kotb3Islam Ismael4Department of Electric Power and Machines, Faculty of Engineering, Zagazig UniversityDepartment of Electric Power and Machines, Faculty of Engineering, Zagazig UniversityDepartment of Electrical Engineering, Faculty of Engineering, Mansoura UniversityDepartment of Electrical Engineering, Faculty of Engineering, Mansoura UniversityDepartment of Electrical Engineering, Faculty of Engineering, Mansoura UniversityAbstract The current study uses the Chernobyl disaster optimizer (CDO), a new metaheuristic optimizer, to identify the seven unknown parameters of solid oxide fuel cells (SOFCs). The procedures of the CDO is based on physical behavior of the elaborated radiations from the well-known Chernobyl disaster according to their mass, speed, frequency, and degree of ionization. The sum of square errors (SMSE) among the estimated and the real measured output voltage datasets of SOFCs is minimized employing the CDO. Set of boundaries of the SOFC’s process is taken into consideration with the problem formulation. SOFCs stack’s model is examined at 800οC and 900οC and its performance is confirmed. The CDO extracts more precise SOFCs’ parameters compared to other competitors. The CDO’s convergence patterns and the SOFCs unit’s performance are studied and proved at steady-state by comparing its results to a number of recognized algorithms under varied operating scenarios. A significant SMSE’s values of 3.46 µV2 and 7.38 µV2 are attained at 800οC and 900οC, respectively by the CDO. As a result, the polarization principal curves of the measured and estimated voltage datasets are checked and verified with very close matching. The dynamic behavior of the SOFCs stack is examined in relation to direct load, electric networks, and superconducting magnetic energy storage devices (SMES) for additional validation and illustration. The role of the SOFCs stack in controlling the active and reactive power delivered to the network and direct load is investigated using two controllers: one to control the inverter, which converts the SOFC’s dc output to the main network, and the other to control the SMES. The Simulink/MATLAB environment is used to indicate the validity of the proposed framework under both steady-state and dynamical conditions. The comprehensive assessments show that the CDO capabilities are very effective when used with microgrids.https://doi.org/10.1038/s41598-025-86493-ySolid oxide fuel cellsUnknown parametersSteady-state modelDynamic performanceOptimization methodsEnergy storage device
spellingShingle Sameh I. Selem
Attia A. El-Fergany
Eid A. Gouda
Mohamed F. Kotb
Islam Ismael
SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer
Scientific Reports
Solid oxide fuel cells
Unknown parameters
Steady-state model
Dynamic performance
Optimization methods
Energy storage device
title SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer
title_full SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer
title_fullStr SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer
title_full_unstemmed SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer
title_short SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer
title_sort sofcs integrated with smes under dynamic power control using chernobyl disaster optimizer
topic Solid oxide fuel cells
Unknown parameters
Steady-state model
Dynamic performance
Optimization methods
Energy storage device
url https://doi.org/10.1038/s41598-025-86493-y
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