journal article·2022-08-23Open access

Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems

Djamel Saba, Fahima Hajjej, Omar Cheikhrouhou, Youcef Sahli, Abdelkader Hadidi, Habib Hamam

Applied Sciences· Volume 12· Issue 17

Abstract

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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Research context

OpenAlex topics: Hybrid Renewable Energy Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Unité de Recherche en Energies Renouvelables en Milieu Saharien, URERMS, Centre de Développement des Energies Renouvelables, CDER, Adrar 01000, Algeria

Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia

CES Laboratory, National School of Engineers of Sfax, University of Sfax, Sfax 3038, Tunisia

Faculty of Engineering, University de Moncton, Moncton, NB E1A3E9, Canada

International Institute of Technology and Management, Commune d’Akanda, Libreville P.O. Box 1989, Gabon

Department of Electrical and Electronic Engineering Science, School of Electrical Engineering, University of Johannesburg, Johannesburg 2006, South Africa

Spectrum of Knowledge Production and Skills Development, Sfax 3027, Tunisia

Funding

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

References (40)

Show source-provided references
1. Urban air pollution, climate change and wildfires: The case study of an extended forest fire episode in northern Italy favoured by drought and warm weather conditions10.1016/j.egyr.2019.11.002 ↗
2. Environmental impact and pollution-related challenges of renewable wind energy paradigm—A review10.1016/j.scitotenv.2019.05.274 ↗
3. De Doile, G.N.D., Rotella Junior, P., Rocha, L.C.S., Bolis, I., Janda, K., and Coelho Junior, L.M. (2021). Hybrid Wind and Solar Photovoltaic Generation with Energy Storage Systems: A Systematic Literature Review and Contributions to Technical and Economic Regulations. Energies, 14.10.3390/en14206521 ↗
4. Optimising photovoltaic-centric hybrid power systems for energy autonomy10.1016/j.egyr.2021.03.039 ↗
5. Optimization of a Multi-source System with Renewable Energy Based on Ontology10.1016/j.egypro.2015.07.787 ↗
6. Experimental analysis of a stand-alone wind-photovoltaic hybrid system in the Sahara Desert10.18280/ejee.210114 ↗
7. Sizing, optimization, control and energy management of hybrid renewable energy system—A review10.1016/j.enbenv.2021.04.002 ↗
8. Nourollahi, R., Tabar, V.S., Zadeh, S.G., and Akbari-Dibavar, A. (2022). A hybrid optimization approach to analyze the risk-constrained operation of a residential hybrid energy system incorporating responsive loads. Comput. Chem. Eng., 157.10.1016/j.compchemeng.2021.107603 ↗
9. Guo, J., Zhang, P., Wu, D., Liu, Z., Ge, H., Zhang, S., and Yang, X. (2021). A new collaborative optimization method for a distributed energy system combining hybrid energy storage. Sustain. Cities Soc., 75.10.1016/j.scs.2021.103330 ↗
10. Sharma, R., Kodamana, H., and Ramteke, M. (2022). Multi-objective dynamic optimization of hybrid renewable energy systems. Chem. Eng. Process. Process Intensif., 170.10.1016/j.cep.2021.108663 ↗
11. Design and Optimization of Hybrid PV-Wind Renewable Energy System10.1016/j.matpr.2017.11.151 ↗
12. Optimal sizing of smart hybrid renewable energy system using different optimization algorithms10.1016/j.egyr.2022.03.197 ↗
13. Optimal sizing of stand-alone hybrid systems based on PV/WT/FC by using several methodologies10.1016/j.joei.2014.03.028 ↗
14. Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system10.1016/j.ijhydene.2014.04.147 ↗
15. GIS-based site selection methodology for hybrid renewable energy systems: A case study from western Turkey10.1016/j.enconman.2013.02.004 ↗
16. Optimal sizing of renewable hybrids energy systems: A review of methodologies10.1016/j.solener.2011.10.016 ↗
17. Contribution to the Management of Energy in the Systems Multi Renewable Sources with Energy by the Application of the Multi Agents Systems “MAS”10.1016/j.egypro.2015.07.792 ↗
18. Hassanien, A., Shaalan, K., Gaber, T., Azar, A., and Tolba, M. (2017). An Energy Management Approach in Hybrid Energy System Based on Agent’s Coordination, Springer.
19. Hassanien, A., Tolba, M., Elhoseny, M., and Mostafa, M. (2018). Development of an Ontology Based Solution for Energy Saving through a Smart Home in the City of Adrar in Algeria, Springer.
20. Multi-agent systems applied for energy systems integration: State-of-the-art applications and trends in microgrids10.1016/j.apenergy.2016.10.056 ↗
21. Amicarelli, E., Tuan, T.Q., and Bacha, S. (2016, January 5–9). Multi-agent system for day-ahead energy management of microgrid. Proceedings of the Power Electronics and Applications EPE’16 ECCE Europe, 2016 18th European Conference, Karlsruhe, Germany.10.1109/EPE.2016.7695257 ↗
22. Elamine, D.O., Nfaoui, E.H., and Jaouad, B. (2015, January 25–26). Multi-agent system based on fuzzy control and prediction using NN for smart microgrid energy management. Proceedings of the 2015 Intelligent Systems and Computer Vision (ISCV), Fez, Morocco.10.1109/ISACV.2015.7105538 ↗
23. Network Topology Independent Multi-Agent Dynamic Optimal Power Flow for Microgrids with Distributed Energy Storage Systems10.1109/TSG.2016.2631600 ↗
24. Raju, L., Rajkumar, I., and Appaswamy, K. (2016, January 24–26). Integrated energy management of micro-grid using multi agent system. Proceedings of the 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS), Pudukkottai, India.10.1109/ICETETS.2016.7603093 ↗
25. Decentralized control of the hybrid electrical system consumption: A multi-agent approach10.1016/j.rser.2015.12.135 ↗
26. Saba, D., Maouedj, R., and Berbaoui, B. (2018, January 26–28). Contribution to the development of an energy management solution in a green smart home (EMSGSH). Proceedings of the 7th International Conference on Software Engineering and New Technologies, Hammamet, Tunisia.10.1145/3330089.3330101 ↗
27. Saba, D., Cheikhrouhou, O., Alhakami, W., Sahli, Y., Hadidi, A., and Hamam, H. (2022). Intelligent Reasoning Rules for Home Energy Management (IRRHEM): Algeria Case Study. Appl. Sci., 12.10.3390/app12041861 ↗
28. Development of new ontological solution for an energy intelligent management in Adrar city
29. Saba, D., Sahli, Y., and Hadidi, A. (2021). An ontology based energy management for smart home. Sustain. Comput. Inform. Syst., 31.10.1016/j.suscom.2021.100591 ↗
30. Hassanien, A. (2019). Design and Development of an Intelligent Ontology-Based Solution for Energy Management in the Home. Machine Learning Paradigms: Theory and Application, Springer.
31. Ontologies: Principles, methods and applications10.1017/S0269888900007797 ↗
32. Hassanien, A., Bhatnagar, R., and Darwish, A. (2021). Contribution to the Realization of a Smart and Sustainable Home, Springer.
33. Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy storage10.1016/j.energy.2018.08.135 ↗
34. Hassanien, A., Shaalan, K., Gaber, T., and Tolba, M. (2018). A Generic Optimization Solution for Hybrid Energy Systems Based on Agent Coordination, Springer.
35. Development of an ontology-based generic optimisation tool for the design of hybrid energy systemsDevelopment of an ontology-based generic optimisation tool for the design of hybrid energy systems10.1504/IJCAT.2017.084773 ↗
36. Degha, H.E., Laallam, F.Z., Said, B., and Saba, D. (2018, January 24–25). Onto-SB: Human Profile Ontology for Energy Efficiency in Smart Building. Proceedings of the 2018 3rd International Conference on Pattern Analysis and Intelligent Systems (PAIS), Tebessa, Algeria.10.1109/PAIS.2018.8598509 ↗
37. PV-TONS: A photovoltaic technology ontology system for the design of PV-systems10.1016/j.engappai.2012.10.010 ↗
38. Figaj, R., Żołądek, M., and Goryl, W. (2020). Dynamic Simulation and Energy Economic Analysis of a Household Hybrid Ground-Solar-Wind System Using TRNSYS Software. Energies, 13.10.3390/en13143523 ↗
39. Antonio Barrozo Budes, F., Valencia Ochoa, G., Obregon, L.G., Arango-Manrique, A., and Ricardo Núñez Álvarez, J. (2020). Energy, Economic, and Environmental Evaluation of a Proposed Solar-Wind Power On-grid System Using HOMER Pro®: A Case Study in Colombia. Energies, 13.10.3390/en13071662 ↗
40. Computational Tools used in Hybrid Renewable Energy Systems Optimization-An overview10.1016/B978-0-12-823377-1.50247-0 ↗