This article presents a contribution to the optimization of a multi sources system with renewable energy system.Following the limits of conventional design methods in the reasoning aspect, also renewable energy hybrid systems are distributed nature, open and includes huge detail information needs a formal representation and a shared conceptualization by dynamic contribution to the change in weather conditions of installation site of hybrid system. We propose an approach based on hybridization between sizing techniques and ontology domain. The introduction of ontology in such systems allows the shared knowledge representation of a common area of a unit. Moreover, these will conceptualization of knowledge that can be updated without changing the system goals.The aim of the work presented in this paper is essentially the conceptualization of the ontology after the presentation of the proposed approach. “Protege2000”is used for editing the ontology. The purpose of this work is a knowledge base which contains a representation of all concepts and informational system details

Given the current energy challenge, renewable energy appear as a real and strategic solution for electricity generation, but the intermittent nature this type of energy we forced to combine at least two power sources to ensure continuity in supply of electricity.Typically multi-source renewable energy systems are managed by centralized approaches, but the limit of these approaches in several aspects such as the dynamic aspect management of system, integration or cancellation of one or more elements we require seek other more reliable approaches for the management of multi-source renewable energy systems.The proposed solution is an integration of Multi Agent Systems “MAS” in energy management, this discipline is the connection of several fields such as artificial intelligence, distributed computing systems and software engineering. “MAS” it is discipline that focuses on collective behaviors produced by the interactions of several autonomous entities called agents, these interactions revolve around cooperation, competition or coexistence between these agents, introducing the issue of collective intelligence and the emergence of structures interactions

Algeria is characterized by extreme cold in winter and high heat and humidity in summer. This leads to an increase in the use of electrical appliances, which has a negative impact on electrical energy consumption and its high costs, especially with the high price of electricity in Algeria. In this context, artificial intelligence can help to regulate the daily consumption of electricity, by optimizing the exploitation of natural resources and alerting the individual to avoid energy wasting. This paper proposes a decision-making tool (IRRHEM) for managing electrical energy at smart home. The IRRHEM solution is based on three elements: the use of natural resources, the notification of the inhabitants in case of resources misuse or wasting behavior, and the aggregation of similar activities at same time. Additionally, based on the proposed intelligent reasoning rules, residents’ behavior and activities are represented by OWL (Ontology Web Language) and written and executed through SWRL (Semantic Web Rule Language). Finally, the (IRRHEM) solution is tested in a home located in Algiers city inhabited by a family of four persons. The IRRHEM performance evaluation results are very promising and show a 3.60% rate of energy saving.

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.

The Tiout oasis is located in the municipality of Naama at the south west of Algeria is known by their ksour, the palm plantations and the good quality of their fruit and vegetables, in particular the dates and its varieties. This area contains enormous capacities of subsoil and superficial water. For several centuries, domestic consumption and the irrigation are carried out by the use of the traditional techniques of water collecting such as; the pendulum wells and foggaras them. Currently, this hydraulic heritage encounters technical and social problems, in particular with the contribution of drillings and the motor- pumps. The main issues are quoted: • Beating and draining of the water sources; • Degradation and abandonment of the traditional techniques. This study objective is to make an inventory of all the water sources in the study area, to study the impact of the modern technologies contribution on the ancestral techniques and finally to propose recommendations for the backup of the hydraulic heritage.