The problematic is to study the management of a hybrid energy system, depending on demand, dedicated to self-governing houses. Energy can be supplied by a photovoltaic panel, a wind turbine and a diesel generator and it can be stored in batteries. The study of this type of systems requires a good control strategy and an effective management. The main objective of this study is to develop a reliable management model and to simulate the hybrid system of a house located in Monastir-Tunisia, with different domestic loads, such as a washing machine, freezer, refrigerator... A system of energy management that can adjust, optimize and adapt the consumption to the available energy resources while satisfying the request is then examined. Thus, to study the problem of energy management and reduce energy consumption and production of greenhouse gases, the definition off an analysis tool on MATLAB/SIMULINK has allowed the covering of load demand in an optimized manner using the optimal system chosen by HOMER.

Les techniques basées sur l'emploi des réseaux de neurones artificiels suscitent au aujourd'hui un intérêt croissant dans les domaines de la commande et de la robotique. La rapidité de traitement, les capacités d'apprentissage et d'adaptation, mais aussi la robustesse de ces approches motivent en grande partie de nombreux travaux dans ce domaine -commande des robots mobiles. Le travail présent a pour but d'utiliser les réseaux des neurones artificiels dans le cadre de la commande des robots mobiles à roues. C'est une étude qui permettra à ces derniers, utilisant des contrôleurs neuronaux artificiels, de suivre une trajectoire de référence préalablement définie.

In this paper, a three-phase shunt active filter is used to compensate for current harmonics and reactive power in three-phase distribution network system. In order to improve its performances, artificial neural networks and fuzzy logic approaches are used to control this device. The first controller, based on ADALINE networks, is used with the direct method in order to identify precisely the necessary currents to reduce the harmonics and to compensate reactive power. The neural network inputs are based on a decomposition of the measured currents. This decomposition is also based on the Fourier series analysis of the current signals and Least Mean Square (LMS) training algorithm to carry out the weights. In this case, three ADALINE are used to extract the fundamental component of the distorted line current directly from the three phase space. The second controller is the fuzzy logic controller, used to …

This paper deals with a real time implementation of a fuzzy logic-based power management of a small scale generation hybrid power system. The system consists of a photovoltaic array and a fuel cell stack, supported by a single-phase grid that supplies a stand-alone AC load. The proposed supervisory algorithm guaranties the system to switch smart between two operation modes, according to the load demand, the gas level and the PV availability. Obviously, the PV side DC–DC converter is controlled to track permanently the maximum power point by using a fuzzy logic MPPT method; whereas, the fuel cell stack and the grid converters are tuned to cover the remaining power, or alternatively, injecting the exceeding power to the utility. Besides, to feed the AC load with a pure sine wave, a Back stepping algorithm is proposed to control the front-end single-phase inverter. To test the effectiveness of the proposed …

The performance of photovoltaic (PV) module is affected by outdoor conditions. Outdoor testing consists installing a module, and collecting electrical performance data and climatic data over a certain period of time. It can also include the study of long-term performance under real work conditions. Tests are operated in URAER located in desert region of Ghardaïa (Algeria) characterized by high irradiation and temperature levels. The degradation of PV module with temperature and time exposure to sunlight contributes significantly to the final output from the module, as the output reduces each year. This paper presents a comparative study of different methods to evaluate the degradation of PV module after a long term exposure of more than 12 years in desert region and calculates uncertainties in measuring. Firstly, this evaluation uses three methods: Visual inspection, data given by Solmetric PVA-600 Analyzer translated at Standard Test Condition (STC) and based on the investigation results of the translation equations as ICE 60891. Secondly, the degradation rates calculated for all methods. Finally, a comparison between a degradation rates given by Solmetric PVA-600 analyzer, calculated by simulation model and calculated by two methods (ICE 60891 procedures 1, 2). We achieved a detailed uncertainty study in order to improve the procedure and measurement instrument.

Temperature, solar insolation, shading and faults affect the performance of the photovoltaic array. Often, the PV arrays get shadowed, completely or partially, by the passing clouds neigh boring buildings, towers or by trees, and other utilities. The situation is of a interest in a case of the large PV power plants. In the case of the shading the characteristics of the PV module are more complex with the several peak values. Under such conditions, it is very difficult to determine the maximum power point (MPP). MATLAB-programmed modelling and simulation of photovoltaic module is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) module and Faults Bypass Diode. The proposed models facilitate simulating the dynamic performances of PV-based power systems and have been validated by means of simulation study. The southern part of Algeria, where the experimental system is mounted, is particularly well appropriate to photovoltaic systems. To evaluate the effectiveness of the proposed model, experiments have been conducted to compare the experimental and simulated current-voltage (IV) and power-voltage (PV) curves of a PV system under some predefined partial shading and faults bypass diode, using different PV technologies such as mono-crystalline and multi-crystalline.

Nowadays, a global interest for renewable energy sources has been growing intensely. In particular, a wind energy has become the most popular. In case of autonomous systems, wind energy conversion system (WECS) based on a double fed induction generator (DFIG) is widely used. In this paper, in order to control the stand-alone system outputs under wind speed and load variations, three kinds of nonlinear control strategies have been proposed, applied and compared, such as: Classical PI controller, Back-Stepping and Sliding Mode controllers. A series of experiments have been conducted to evaluate and to compare the developed controllers’ dynamic performances under load demand and speed variations. The design and the implementation of different control strategies to a 1.5kW doubly fed induction machine is carried out using a dSpace DS1104 card based on MATLAB/Simulink environment …

This paper proposes a robust sliding mode control of grid-connected brushless doubly fed induction generator (BDFIG). The developed algorithm is based on the decoupling control by using oriented grid flux vector control strategy. The decoupling of the active and the reactive stator powers insures an optimal performance of the BDFIG at the sub-synchronous region. The stability analysis of the closed-loop system is rigorously proved using a Lyapunov approach. The robustness of the proposed control with respect to parameter variation is illustrated by simulation results. Furthermore, a maximum power point tracking strategy is added to enhance the wind energy conversion system efficiency.