Majlesi Journal of Energy Management
Volume:10 Issue: 4, Dec 2021

Generally, the switch mode power supply input voltage source is constant or shows insignificant little varieties.in any case, when fuel call used input source the last assumption is not valid. A fuel cell stack is give a details of low and not controlled DC output voltage, moreover, when the demanded current increases the output voltage becomes low in a nonlinear form; from now on, suitable controller is required to taken the previously mentioned issues. In this article, a normal current-mode controller is planned to using a joined model for an energy unit stack and a boost converter; besides, the resolving control method increasing the system stability and output voltage regulation. The proposed energy system utilizes an energy component power (polymer electrolyte film fuel cell) and a boost converter passing on power of 900 W. the proposed controller execution for output voltage regulation by means of closed loop gain estimations and step load changes. What's more, a correlation amongst open-and closed- loop estimations is made, where the controller robustness is tried for vast load varieties and fuel cell stack output voltage changes are shows on simulation results.

In this article, we present the construction of observers of rotor flux and mechanical speed needed for robust control of the induction machine. Two observers will be developed for comparison. The first is based on the techniques MRAS and the second is observer of KUBOTA, with the enhanced DTC-ANN (by artificial intelligence), "sensorless DTC". The validity of the proposed methods is confirmed by the simulation results. This work is devoted to the construction of rotor flux observers and the mechanical speed necessary for the robust control of the induction machine. Two speed observers will be developed for comparison. The first is based on the MRAS technique and the second is based on KUBOTA, with the improved DTC-ANN control "sensorless DTC control». The THD (Total Harmonic Distortion) of stator current, torque ripple and stator flux ripple are determined and compared with conventional DTC control scheme using Matlab/Simulink environment.

This paper suggests an Artificial Neural Network model (ANN) in order to increase propulsion capability and reduce fuel consumption in hybrid electric vehicles. All stages are implemented by Simulink of MATLAB software. The simulation is based on basic parameters of internal-combustion engine. The achieved results reveal the ability of suggested method to reduce fuel consumption and increase the lifetime of the vehicle components, including the battery due to reduction of travel disturbances and soft moving of the vehicle at different speeds. It is also possible to optimize the problem for various vehicles and all types of roads by changing the motion parameters and conditions of artificial Neural Network Parameterization.

Conversion of solar light into silicon photovoltaic cells into electrical energy create significant efficiency losses; physical and technological. Studies on the physical characteristics of photovoltaic cell materials show that technological losses such as considerable reflection and modest absorption efficiency can be minimized. In this work, we propose a new structure that is based on a planar metamaterial waveguide; this guide can contribute to the optimization of the performance of photovoltaic silicon cells. Our proposed structure is a novel approach to anti-reflective coating devices used to achieve high absorption in silicon solar cells. The planar guide; deposited on the silicon layer consists of a network of metamaterial Split Ring Resonators (SRRs) which have a magnetic resonance due to a negative permeability (). The incidence of electromagnetic waves on our structure is made according to the electric transverse modes (TE) for various inclination values (). The geometrical shape of the (SRRs) and the substrate on which they are engraved are chosen to have maximum absorption, whereas the reflection, transmission and absorption coefficients will be represented as a function of the associated wavelength for different values of the incidence. To simulate our structure which is quite complicated, we will use Ansoft HFSS commercial software.

In this paper, the model predictive control is designed to control the frequency in a micro grid in the island mode with respect to the disturbances entered into the system. One of the important issues in the micro grid is controlling the frequency in it. In case of turbulence in the micro grid, when the micro grid is connected to the network, and also in island mode, it changes the frequency of the system. The proposed micro grid is intended for three areas and in order to improve its efficiency, the particle swarm optimization algorithm is used to determine the controller parameters such as prediction horizon, control horizon, sampling time and etc…

In this article, the author proposes a sensorless direct torque control (DTC) of permanent magnet synchronous motor (PMSM) fed by four-level neutral point diode clamped (NPC) inverter using a neural networks (NNs) technique. neural PI (PIN) regulator is used for controlling the rotor speed of PMSM and NN controller applied in switching select stator voltage. The technique proposed in this article can minimize the stator flux ripple, electromagnetic torque ripple and harmonic distortion of stator current, and especially improve system good dynamic performance and robustness in high and low speeds.