Citation: Saba, D.; Hajjej, F.;
Cheikhrouhou, O.; Sahli, Y.; Hadidi,
A.; Hamam, H. Development of an
Intelligent Solution for the
Optimization of Hybrid Energy
Systems. Appl. Sci. 2022, 12, 8397.
https://doi.org/10.3390/
app12178397
Academic Editors: Luis
Hernández-Callejo, Sergio
Nesmachnow and Sara Gallardo
Saavedra
Received: 5 July 2022
Accepted: 8 August 2022
Published: 23 August 2022
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Article
Development of an Intelligent Solution for the Optimization of
Hybrid Energy Systems
Djamel Saba
1,
* , Fahima Hajjej
2
, Omar Cheikhrouhou
3
, Youcef Sahli
1
, Abdelkader Hadidi
1
and Habib Hamam
4,5,6,7
1
Unité de Recherche en Energies Renouvelables en Milieu Saharien, URERMS, Centre de Développement des
Energies Renouvelables, CDER, Adrar 01000, Algeria
2
Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint
Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
3
CES Laboratory, National School of Engineers of Sfax, University of Sfax, Sfax 3038, Tunisia
4
Faculty of Engineering, University de Moncton, Moncton, NB E1A3E9, Canada
5
International Institute of Technology and Management, Commune d’Akanda, Libreville P.O. Box 1989, Gabon
6
Department of Electrical and Electronic Engineering Science, School of Electrical Engineering, University of
Johannesburg, Johannesburg 2006, South Africa
7
Spectrum of Knowledge Production and Skills Development, Sfax 3027, Tunisia
* Correspondence: saba_djamel@yahoo.fr
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.
Keywords:
decision-making tool; intelligent reasoning rules; energy saving; energy domain ontology;
hybrid energy system
1. Introduction
Air pollution, climate change, and limited fossil resources have raised awareness
that sustainable development that takes care of the environment in which we live is
necessary [
1
]. With the difficulty of connecting electricity grids to remote areas, RE presents
a good alternative to fossil fuels, it does not emit greenhouse gases, and it allows the
decentralized production of resources [
2
]. However, the random specificity of energy
sources imposes special rules for the optimization and operation of energy systems. In
addition, the hybridization between some of the RE sources forms a complementarity of
energy production and an alternative to conventional generators generally used to produce
electricity. An HES design is an important step because of its relationship to completion
Appl. Sci. 2022, 12, 8397. https://doi.org/10.3390/app12178397 https://www.mdpi.com/journal/applsci
