A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation

The solar photovoltaic (PV) energy has an important place among the renewable energy sources. Therefore, several researchers have been interested by its modelling and its prediction, in order to improve the management of the electrical systems which include PV arrays. Among the existing techniques, artificial neural networks have proved their performance in the prediction of the solar radiation. However, the existing neural network models don't satisfy the requirements of certain specific situations such as the one analyzed in this paper. The aim of this research work is to supply, with electricity, a race sailboat using exclusively renewable sources. The developed solution predicts the direct solar radiation on a horizontal surface. For that, a Nonlinear Autoregressive Exogenous (NARX) neural network is used. All the specific conditions of the sailboat operation are taken into account. The results show that the best prediction performance is obtained when the training phase of the neural network is performed periodically

Management Approach for Microgrid Operation Using Multi Agent System (MAS) Technique

The integration of renewable energies in the electrical grid and the shift to a distributed structure of the grid had made the control operation extremely complicated. This complexity has prompted researchers to take an interest in the conception of smart interfaces in order to manage the operation of microgrids. This paper proposes an approach of microgrid management using the Multi Agent System (MAS) technique. Based on the distributed nature of MAS and their ability to communicate heterogeneous entities with each other's, the studied approach consists in ensuring the adequate interactions between the concerned agents in order to perform two microgrid operation modes: the first one is the operation of the microgrid without connection with the main grid. In this case, the balance between supply and demand of energy must be achieved. The second operation mode consists on the sale and the purchase of electricity to/from the neighbors' microgrids and the main grid

Study and development of a methodology for driving micro-network distributed systems : Application to power to gas as new energy conversion and storage architectures.

Nos travaux s’inscrivent dans le contexte global de la transition énergétique et de l’émergence des micro-réseaux, et de leur capacité, à terme, d’intégrer la production distribuée d’énergie tout en assurant la stabilité et la qualité du service. Parmi les technologies émergentes, les procédés Power-To-Gaz et en particulier le Power-to-Methane que nous étudions ici (production de CH4 à partir de l’électricité, en passant par H2 et CO2) ont l’avantage : d’absorber le surplus de production électrique, de récupérer et valoriser les émissions de CO2, et d’offrir des capacités de stockage importantes et de longue durée.Notre problématique porte sur la modélisation et la simulation d’un système PtM avec comme objectif d’assurer la continuité d’alimentation en CH4, ainsi que la sécurité du système en fonctionnement.Dans un premier temps nous effectuons le choix de technologies adaptées afin de déterminer la structure d’un système PtM avant de dimensionner ce système. Nous nous appuyons sur la modélisation REM (Représentation Energétique Macroscopique) pour intégrer les comportements physiques des équipements du système en régime stationnaire, mais également en régime transitoire, en prenant en compte des phases comme : le démarrage, le préchauffage…, et ainsi simuler le fonctionnement de ce système.Dans un second temps, nous développons une stratégie de gestion d’énergie multiniveaux afin de garantir le bon fonctionnement des équipements et du système dans sa globalité. Nous choisissons de la mettre en œuvre à travers la proposition d’un système multi-agents (SMA) et nous modélisons chacun des agents. Nous implémentons partiellement ce SMA et nous le simulons en connexion avec le modèle REM du système PtM pour montrer la faisabilité de notre approche.Our work is concerned with energy transition and the emergence of micro-grids and their ability to integrate distributed power generation while at the same time ensure stability and service quality. Among the emerging technologies, the Power to Gas process and in particular the Power to Methane process which we are addressing here (production of CH4 from electricity, via H2 and CO2), have the advantage of absorbing surplus of electricity production, recovering CO2 emissions, as well as offering significant and long-term storage capacity.Our concern was in relation to the modeling and simulation of a PtM system with the objective of ensuring the continuity of CH4 supply and ensuring the safety of the system in operation.First, we chose the appropriate technologies to determine the structure of a PtM system before sizing this system. We utilised the REM modeling (Energetic Macroscopic Representation) to integrate the physical behaviors of the equipment of the system in a steady state, and in a transient state, taking into account phases like starting, preheating…, and ultimately the simulation of the operation system.In the second phase, we developed a multilevel energy management strategy to ensure the proper working order of each piece of equipment and of the global system. We chose to implement it through a multi-agent system (MAS) and we modeled each one of the agents. We partially implemented the MAS and simulated it with the REM model of the PtM system to show the feasibility of our approach