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Ninet M. A. El-Rahman
Electronics Research Institute
Computer Science & IT

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Optimization and Feasibility Analysis of Satellite Earth Station Power System Using Homer Hanaa T. El-Madany; Faten H. Fahmy; Ninet M. A. El-Rahman; Hassen T. Dorrah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 2: June 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i2.812

Abstract

Satellite earth stations which located in remote areas are one of many applications powered by the renewable energy sources. Ground system consists of ground station and control centers working together to support the spacecraft and the data user. Earth station consists of major subsystems, transmitter, receiver, antenna, tracking equipment, terrestrial interface equipment and power supply. Power subsystem is an important part that required for supplying the earth station with electrical power to continue communicating with its remote sensing satellite. This paper deals with simulation and optimal sizing of earth station power system using HOMER software. A combination of two energy sources (solar, and wind) to provide a continuous electric power production is used to determine the optimum system operation. Three system configurations are compared with respect to the total net present cost (NPC) and levelized cost of energy (COE). Also, economical study will be analyzed for energy demand and sensitivity analysis will be performed.
Design of FPGA Based Neural Network Controller for Earth Station Power System Hanaa T. El-Madany; Faten H. Fahmy; Ninet M. A. El-Rahman; Hassen T. Dorrah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 2: June 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i2.796

Abstract

Automation of generating hardware description language code of neural networks models can highly decrease time of implementation those networks into a digital devices, thus significant money savings. To implement the neural network into hardware design, it is required to translate generated model into device structure. VHDL language is used to describe those networks into hardware. VHDL code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic of the earth station and the satellite power systems using ModelSim® PE 6.6 simulator tool. Integration between MATLAB® and VHDL is used to save execution time of computation. The results shows that a good agreement between MATLAB and VHDL and a fast and flexible feed forward NN which is capable of dealing with floating point arithmetic operations; minimum number of CLB slices; and good speed of performance. FPGA synthesis results are obtained with view RTL schematic and technology schematic from Xilinix tool. Minimum number of utilized resources is obtained by using Xilinix VERTIX5. 
Co-Authors Faten H. Fahmy Hanaa T. El-Madany Hassen T. Dorrah