Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems
This paper presents a proposal for the development of a new intelligent solution for the optimization of hybrid energy systems. This solution is of great importance for installers of hybrid energy systems, as it helps them obtain the best configuration of the hybrid energy system (efficient and less...
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MDPI AG
2022-08-01
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author | Djamel Saba Fahima Hajjej Omar Cheikhrouhou Youcef Sahli Abdelkader Hadidi Habib Hamam |
author_facet | Djamel Saba Fahima Hajjej Omar Cheikhrouhou Youcef Sahli Abdelkader Hadidi Habib Hamam |
author_sort | Djamel Saba |
collection | DOAJ |
description | This paper presents a proposal for the development of a new intelligent solution for the optimization of hybrid energy systems. This solution is of great importance for installers of hybrid energy systems, as it helps them obtain the best configuration of the hybrid energy system (efficient and less expensive). In this solution, it is sufficient to enter the name of the location of the hybrid energy system that we want to install; after that, the solution will show the name of the best technology from which the optimal configuration of this system can be obtained. To accomplish this goal, the study relied on the ontology approach for two reasons, one of which is related to the nature of hybrid systems, because it is characterized by a large amount of information that requires good structuring, and the second reason is the interaction of hybrid energy systems with the external environment (climate, site characteristics). Afterward, to develop the knowledge base of the ontology, many steps were followed, the first of which is related to a detailed study of the existing one and the extraction of the basic elements, such as the concepts and the relations between them, followed by the development of the rules of intelligent reasoning, which is an interaction between the elements of the ontology through which all possible cases are treated. The “Protégé” software was used to edit these elements and perform the simulation process to show the results of the developed solution. Finally, the paper includes a case study, and the results show the importance of the developed solution, and it is open to future developments. |
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issn | 2076-3417 |
language | English |
last_indexed | 2024-03-10T03:06:37Z |
publishDate | 2022-08-01 |
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spelling | doaj.art-72dfe4a9b4c84b4fa1f0ec5f2d45b4402023-11-23T12:38:51ZengMDPI AGApplied Sciences2076-34172022-08-011217839710.3390/app12178397Development of an Intelligent Solution for the Optimization of Hybrid Energy SystemsDjamel Saba0Fahima Hajjej1Omar Cheikhrouhou2Youcef Sahli3Abdelkader Hadidi4Habib Hamam5Unité de Recherche en Energies Renouvelables en Milieu Saharien, URERMS, Centre de Développement des Energies Renouvelables, CDER, Adrar 01000, AlgeriaDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaCES Laboratory, National School of Engineers of Sfax, University of Sfax, Sfax 3038, TunisiaUnité de Recherche en Energies Renouvelables en Milieu Saharien, URERMS, Centre de Développement des Energies Renouvelables, CDER, Adrar 01000, AlgeriaUnité de Recherche en Energies Renouvelables en Milieu Saharien, URERMS, Centre de Développement des Energies Renouvelables, CDER, Adrar 01000, AlgeriaFaculty of Engineering, University de Moncton, Moncton, NB E1A3E9, CanadaThis paper presents a proposal for the development of a new intelligent solution for the optimization of hybrid energy systems. This solution is of great importance for installers of hybrid energy systems, as it helps them obtain the best configuration of the hybrid energy system (efficient and less expensive). In this solution, it is sufficient to enter the name of the location of the hybrid energy system that we want to install; after that, the solution will show the name of the best technology from which the optimal configuration of this system can be obtained. To accomplish this goal, the study relied on the ontology approach for two reasons, one of which is related to the nature of hybrid systems, because it is characterized by a large amount of information that requires good structuring, and the second reason is the interaction of hybrid energy systems with the external environment (climate, site characteristics). Afterward, to develop the knowledge base of the ontology, many steps were followed, the first of which is related to a detailed study of the existing one and the extraction of the basic elements, such as the concepts and the relations between them, followed by the development of the rules of intelligent reasoning, which is an interaction between the elements of the ontology through which all possible cases are treated. The “Protégé” software was used to edit these elements and perform the simulation process to show the results of the developed solution. Finally, the paper includes a case study, and the results show the importance of the developed solution, and it is open to future developments.https://www.mdpi.com/2076-3417/12/17/8397decision-making toolintelligent reasoning rulesenergy savingenergy domain ontologyhybrid energy system |
spellingShingle | Djamel Saba Fahima Hajjej Omar Cheikhrouhou Youcef Sahli Abdelkader Hadidi Habib Hamam Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems Applied Sciences decision-making tool intelligent reasoning rules energy saving energy domain ontology hybrid energy system |
title | Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems |
title_full | Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems |
title_fullStr | Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems |
title_full_unstemmed | Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems |
title_short | Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems |
title_sort | development of an intelligent solution for the optimization of hybrid energy systems |
topic | decision-making tool intelligent reasoning rules energy saving energy domain ontology hybrid energy system |
url | https://www.mdpi.com/2076-3417/12/17/8397 |
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