Optimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligence

Abstract In recent years, small-scale nuclear power plants, particularly micro nuclear reactors, have emerged as viable alternatives, gaining importance in the technical and economic operation of electrical distribution systems. As consumer demand for electricity continues to rise, the use of renewa...

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Main Authors: Samira M. Nassar, A. A. Saleh, Ayman A. Eisa, E. M. Abdallah, Ibrahim A. Nassar
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-11049-z
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author Samira M. Nassar
A. A. Saleh
Ayman A. Eisa
E. M. Abdallah
Ibrahim A. Nassar
author_facet Samira M. Nassar
A. A. Saleh
Ayman A. Eisa
E. M. Abdallah
Ibrahim A. Nassar
author_sort Samira M. Nassar
collection DOAJ
description Abstract In recent years, small-scale nuclear power plants, particularly micro nuclear reactors, have emerged as viable alternatives, gaining importance in the technical and economic operation of electrical distribution systems. As consumer demand for electricity continues to rise, the use of renewable energy sources and nuclear energy has become essential, especially as dependence on conventional energy sources grows increasingly unsustainable from an environmental standpoint. In this study, mathematical models for various Hybrid Energy Systems (HES) are developed using both single and multi-objective functions. Active Power Loss (APL) is selected as the first single-objective fitness function, while the total Net Present Cost (NPC) serves as the second. These two objectives are also considered together in a multi-objective optimization framework. The White Shark Optimizer is employed to determine the optimal configuration that achieves an improved voltage profile, reduces power losses, and minimizes both cost and greenhouse gas (GHG) emissions. The proposed modeling and simulations are conducted using MATLAB software, and the optimization methodology is applied to three types of HES on two standard radial distribution networks; the IEEE 33-bus and IEEE 69-bus systems. The three HES configurations analyzed are; Nuclear-Renewable Hybrid Energy System (N-R HES), Stand-alone Fossil Fuel-based Thermal Generators (FFTGs), and Renewable-Fossil Fuel Hybrid Energy System. Among the three, the N-R HES demonstrates the most favorable between system performance, cost efficiency, and environmental impact. Results and analysis prove that N-R HES is the most effective solution for sustainable energy generation and decarbonization, offering the lowest NPC and APL.
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spelling doaj-art-b1b5ea3c551347768890a4d8a3a43f482025-08-20T03:42:41ZengNature PortfolioScientific Reports2045-23222025-07-0115112410.1038/s41598-025-11049-zOptimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligenceSamira M. Nassar0A. A. Saleh1Ayman A. Eisa2E. M. Abdallah3Ibrahim A. Nassar4Department of Nuclear Safety and Radiological Emergencies, NCRRT, Egyptian Atomic Energy AuthorityDepartment of Nuclear Safety and Radiological Emergencies, NCRRT, Egyptian Atomic Energy AuthorityDepartment of Nuclear Safety and Radiological Emergencies, NCRRT, Egyptian Atomic Energy AuthorityDepartment of Electrical Engineering, Faculty of Engineering, Al-AzharUniversityDepartment of Electrical Engineering, Faculty of Engineering, Al-AzharUniversityAbstract In recent years, small-scale nuclear power plants, particularly micro nuclear reactors, have emerged as viable alternatives, gaining importance in the technical and economic operation of electrical distribution systems. As consumer demand for electricity continues to rise, the use of renewable energy sources and nuclear energy has become essential, especially as dependence on conventional energy sources grows increasingly unsustainable from an environmental standpoint. In this study, mathematical models for various Hybrid Energy Systems (HES) are developed using both single and multi-objective functions. Active Power Loss (APL) is selected as the first single-objective fitness function, while the total Net Present Cost (NPC) serves as the second. These two objectives are also considered together in a multi-objective optimization framework. The White Shark Optimizer is employed to determine the optimal configuration that achieves an improved voltage profile, reduces power losses, and minimizes both cost and greenhouse gas (GHG) emissions. The proposed modeling and simulations are conducted using MATLAB software, and the optimization methodology is applied to three types of HES on two standard radial distribution networks; the IEEE 33-bus and IEEE 69-bus systems. The three HES configurations analyzed are; Nuclear-Renewable Hybrid Energy System (N-R HES), Stand-alone Fossil Fuel-based Thermal Generators (FFTGs), and Renewable-Fossil Fuel Hybrid Energy System. Among the three, the N-R HES demonstrates the most favorable between system performance, cost efficiency, and environmental impact. Results and analysis prove that N-R HES is the most effective solution for sustainable energy generation and decarbonization, offering the lowest NPC and APL.https://doi.org/10.1038/s41598-025-11049-zNuclear energy sourceRenewable energy sourcesOptimization technique
spellingShingle Samira M. Nassar
A. A. Saleh
Ayman A. Eisa
E. M. Abdallah
Ibrahim A. Nassar
Optimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligence
Scientific Reports
Nuclear energy source
Renewable energy sources
Optimization technique
title Optimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligence
title_full Optimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligence
title_fullStr Optimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligence
title_full_unstemmed Optimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligence
title_short Optimal planning of integrated nuclear-hybrid renewable energy systems for electrical distribution networks based on artificial intelligence
title_sort optimal planning of integrated nuclear hybrid renewable energy systems for electrical distribution networks based on artificial intelligence
topic Nuclear energy source
Renewable energy sources
Optimization technique
url https://doi.org/10.1038/s41598-025-11049-z
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