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Prof. Abdel-Salam Hafez Abdel-Salam Hamza :: Publications:

Title:
Optimum Design of Substation Grounding Grid Based on Grid Balancing Parameters using Genetic Algorithm
Authors: Abdelsalam Hafez, Abdelrahman Said, Ahmed Taher, Tamer Eliyan
Year: 2018
Keywords: Keywords—Grid design, Grid resistance, Mesh voltage, Step voltage, Genetic Algorithm, Weight Factors.
Journal: 2018 Twentieth International Middle East Power Systems Conference (MEPCON), IEEE, Cairo University, Egypt.2018.
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: 2018 Twentieth International Middle East Power Systems Conference (MEPCON), IEEE, Cairo University, Egypt.2018.
Local/International: Local
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

Abstract—Substation is the most vital part of electrical power system that should be operated continually and safely. Ground grid is installed to help detecting ground faults and assure safety of persons. In this paper IEEE 80-2013 was utilized to make optimum design of substation ground grid. A new cost function was proposed which is based on the effective factors that affect grid performance. These factors include number of horizontal conductors, cross-sectional area of these conductors, grid burial depth, number of ground rods, length of each rod and surface material thickness. MATLAB software was used to design, study and analyze the whole parameters affecting the grid performance. The study of each of the mentioned parameters has been used to develop weight factors based on the effect of each parameter upon the grounding grid performance represented in grounding grid resistance, mesh voltage and step voltage. These weight factors were used in conjunction with the proposed cost function to aid the search for the optimum design of the grid. Genetic Algorithm (GA) utilized this function to minimize the cost of the grid and avoid over designing. This study was carried out on Future substation 220/22 kV located in Egypt. Results show that the use of cost function only is not sufficient to give a reasonable optimum design and the use of weight factors gives better and more realistic options for optimum design.

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