فهرست مطالب

  • Volume:7 Issue: 1, Mar 2018
  • تاریخ انتشار: 1398/03/11
  • تعداد عناوین: 4
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  • Habib Benbouhenni * Pages 11-19
    A permanent magnet synchronous generator (PMSG) is a generator where the excitation field is provided by a permanent magnet instead of a coil. In this work space vector modulation (SVM) method using artificial neural network (ANN) on the stator side converter of a 6KW PMSG controlled by direct power control (DPC). In this article, the converter is controlled by a new SVM technique in order to minimize the total harmonic distortion (THD) and powers ripples (active and reactive). The validity of the proposed strategy applied on the PMSG is verified by Matlab/Simulink. On the other hand, the reactive power, stator current, active power is determined and compared with conventional command strategy.
    Keywords: PMSG, SVM, ANN, THD, DPC
  • Sayed Abdolhossein Emadi *, Mohammad Reza Zare Pages 21-27
    In this paper by using the nonlinear structure for model the solar cell, the voltage and the desired power as the solar cell output are provided. The optimal operating point for power of solar cell system is called the maximum power point and varies in different conditions. In order to achieve this goal, the DC / DC converter is boost converter, which controls by its switching. Fuzzy theory has been used to achieve optimal power for load and maximum solar cell power. In this paper, the fuzzy algorithm is also used to optimize the control method. Changes in output load and amount of sunlight are among the issues in which the stability of the control system is analyzed. The results are presented according to the simulation in MATLAB software and the good performance of the controller is shown in different conditions of the system's performance.
    Keywords: Solar CellTracking Maximum PowerAdaptive Smart Controller Chart
  • Determining the location and capacity of combined heat and power generation units (CHP) andstatic voltage compensator (SVC) in energy hub
    Mehdi Rezaeiheydari, Ehsan Esfandiyari Page 36
    The purpose of present study was to optimal positioning of SVC and CHP simultaneously, in a way that lead to highest profit and the lowest losses in the system.This method increases the efficiency of entire transmission system and has a significant effect on the power quality and energy hub. For this purpose, neural network method was used to optimize energy cost and hub.Neural network is considered as an intelligent and efficient method of optimization and the results of simulations indicated the effectiveness of the method in optimized positioning
    Keywords: power generation units, CHP
  • Optimal DG Sizing and Siting in Radial System Using Hybridization of GSA and Firefly algorithms
    Rajesh Kumar Samala_Mercy Rosalina K dr Page 37
    In order to improve the Voltage Stability Index (VSI), real and reactive power loss compensation, there is a solution in terms of Distributed Generation (DG). By incorporating DGs at proper location with suitable size the power losses will be reduced and there is an improvement of voltage profile. For this a new approach was introduced which is a hybridization of Firefly Algorithm (FA) with Gravitational Search Algorithms (GSA). After finding the real power losses using conventional method like Backward/Forward (BW/FW) sweep approach, the new approach was implemented to prove that it was the better algorithm than the other approaches. All these approaches have been implemented on standard IEEE-33 radial test system. MATLAB software was used to simulate the results and to find optimal DG sizing and siting on IEEE-33 test system.
    Keywords: BW-FW sweep approach, GSA approach, FA, Power Losses