Introduction. This article deals with the optimization of the energy conversion of a grid-connected photovoltaic system. The novelty is to develop an intelligent maximum power point tracking technique using artificial neural network algorithms. Purpose. Intelligent maximum power point tracking technique is developed in order to improve the photovoltaic system performances under the variations of the temperature and irradiation. Methods. This work is to calculate and follow the maximum power point for a photovoltaic system operating according to the artificial intelligence mechanism is and the latter is used an adaptive modified perturbation and observation maximum power point tracking algorithm based on function sign to generate an specify duty cycle applied to DC-DC converter, where we use the feed forward artificial neural network type trained by Levenberg-Marquardt backpropagation. Results. The photovoltaic system that we chose to simulate and apply this intelligent technique on it is a stand-alone photovoltaic system. According to the results obtained from simulation of the photovoltaic system using adaptive modified perturbation and observation – artificial neural network the efficiency and the quality of the production of energy from photovoltaic is increased. Practical value. The proposed algorithm is validated by a dSPACE DS1104 for different operating conditions. All practice results confirm the effectiveness of our proposed algorithm.
Introduction. Internal combustion engine technology has been considered for the alternator system in the last two decades. Especially when considering fuel diversity, reliability, portability, power density, research studies are increasing day by day. In this respect, interest has been focused on linear generator studies. Purpose. The goal of the research is to investigate the performance of a linear generator and its application to generate electrical energy from an internal combustion engine to solve the range problem of small electric powered vehicles. The generator, unlike a traditional generator, consists of a linear generator with a crank mechanism driven by an internal combustion engine. Originality. The configuration of the linear generator with internal combustion engine crank has not previously been reported. Methods. The numerical solution of the generator was carried out by the finite element method in the Ansys Maxwell software in a cylindrical coordinate system. The effect of stroke length and frequency on voltage and output power was investigated by monitoring an external electrical load. A prototype linear generator has been designed and produced considering the sizing dimensions. The configuration can be used in power-hungry applications and increase the range of small electric vehicles. Results. The results from simulation and practice are largely in agreement. Practical value. A practical mechanical system was built comprising a linear generator connected to a 2.2 kW internal combustion engine via a crank connecting rod for analysis.
In this paper we interested to the study the necessary of Facts to increase the transient stability on the presence of faults and the integration of new renewable source, like wind energy, these lasts make the electrical grid operate in a new conditions, the STATCOM is one of the important Facts element, It provides the desired reactive-power generation and absorption entirely by means of electronic processing of the voltage and current waveforms in a voltage source converter (VSC). This function is identical to the synchronous condenser with rotating mass. In present work we propose a transient stability improvement using STATCOM under faults, in the first time we study the transient stability with and without STATCOM for clearly his advantages. In the second time we know the relation between the reactive power injecting by a STATCOM and the critical clearing time, some simulation results are given, commented and discussed.
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