Soumia El Hani

Dans le présent article, nous discutons le problème de la recherche de la puissance maximum d’une éolienne, (Maximum Power Point Tracking, ‘MPPT’), à base d’une Génératrice Synchrone à Aimant Permanant (PMSG) débitant dans le réseau de puissance à travers une chaîne complète de convertisseurs statiques. Pour cela, nous proposons un schéma de commande de la machine synchrone, comportant un premier dispositif alternatif/continu suivi d’un second dispositif continu/alternatif. Le principe MPPT repose sur la variation de vitesse de la turbine suivant celle du vent en cas de raccordement indirect de la génératrice avec le réseau. Les simulations sur Matlab-Simulink, présentées en fin d’article, confirment une bonne adéquation du schéma de commande, du choix des paramètres de réglage ainsi que l’architecture de la chaîne de conversion aux objectifs assignés.

The process of thermal control and regulation in buildings is considered complex. Its complexity lies in the various internal and external physical phenomena impacting its control, and also in the increasingly important requirements of occupant comfort, energy optimization and efficiency, and optimization of measuring and monitoring equipment. Recently, the establishment of technical rules for optimal building thermal control has gained interest in academia and industry. These rules have focused mainly on three aspects: the use of renewable energy, optimal management, and the use of equipment and materials allowing the optimization of energy. However, optimal control has not been addressed enough. In this article, we present a PID controller based on a Neural Network approach for thermal building management and control. The proposed approach is based on two processes: an optimal identification process dedicated to the thermal building behavior prediction impacted by variable and invariable elements, measured and unmeasured factors, and a control process to ensure the desired performance with optimal energy control. The results obtained show the advantages of the adopted system in terms of energy optimization, with an important energy gain of 8% to 11%, along with better regulation and control performance, and in terms of occupant comfort with minimal temperature variations.

Modeling and Robust Control of a Grid Connected Direct Driven PMSG Wind Turbine By ADRC