Optimal Power Cable for Smart Grids

Adel El-Shahat; Vincent Faison Ii; Rami J. Haddad; Mohammad Ahad

doi:10.1109/SoutheastCon42311.2019.9020566

Optimal Power Cable for Smart Grids

Adel El-Shahat
, Vincent Faison Ii
, Rami J. Haddad
, Mohammad Ahad

Electrical & Computer Engineering

Georgia Southern University

Research output: Contribution to book or proceeding › Conference article › peer-review

Abstract

This paper investigates the calculation of ampacity values of medium voltage cable in an unfavorable burial method. The ampacity values are obtained using the International Electro-technical Commission (IEC) 60287 for all ac voltages with a 100% load factor in ducts, pipes, trenches. The cables are obtained from Leading Solution (LS) cable data sheet which provides the values for parameters needed to calculate the ampacity. The ampacity values are analyzed with constant and varying ambient temperature and burial depth. An Artificial Neural Network (ANN) is created to allow users to input a cables voltage and ampacity values in different situations to obtain an output of parameters for that specific cable. Ampacity value calculations showed an 8-15% difference from listed to those calculated. The regression factor of the ANN was around 0.996 and the overall error for all fourteen outputs was at maximum between 1-2%.

Original language	English
Title of host publication	2019 IEEE SoutheastCon, SoutheastCon 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728101378
DOIs	https://doi.org/10.1109/SoutheastCon42311.2019.9020566
State	Published - Apr 2019
Event	2019 IEEE SoutheastCon, SoutheastCon 2019 - Huntsville, United States Duration: Apr 11 2019 → Apr 14 2019

Publication series

Name	Conference Proceedings - IEEE SOUTHEASTCON
Volume	2019-April
ISSN (Print)	1091-0050
ISSN (Electronic)	1558-058X

Conference

Conference	2019 IEEE SoutheastCon, SoutheastCon 2019
Country/Territory	United States
City	Huntsville
Period	04/11/19 → 04/14/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Scopus Subject Areas

Computer Networks and Communications
Software
Electrical and Electronic Engineering
Control and Systems Engineering
Signal Processing

Keywords

Ampacity
Cables
International Electro-technical Commission
Medium voltage
Neural Networks

Access to Document

10.1109/SoutheastCon42311.2019.9020566

Cite this

@inproceedings{de23a376ab8a4c4cba8763e8562b414b,

title = "Optimal Power Cable for Smart Grids",

abstract = "This paper investigates the calculation of ampacity values of medium voltage cable in an unfavorable burial method. The ampacity values are obtained using the International Electro-technical Commission (IEC) 60287 for all ac voltages with a 100\% load factor in ducts, pipes, trenches. The cables are obtained from Leading Solution (LS) cable data sheet which provides the values for parameters needed to calculate the ampacity. The ampacity values are analyzed with constant and varying ambient temperature and burial depth. An Artificial Neural Network (ANN) is created to allow users to input a cables voltage and ampacity values in different situations to obtain an output of parameters for that specific cable. Ampacity value calculations showed an 8-15\% difference from listed to those calculated. The regression factor of the ANN was around 0.996 and the overall error for all fourteen outputs was at maximum between 1-2\%.",

keywords = "Ampacity, Cables, International Electro-technical Commission, Medium voltage, Neural Networks",

author = "Adel El-Shahat and Ii, \{Vincent Faison\} and Haddad, \{Rami J.\} and Mohammad Ahad",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE SoutheastCon, SoutheastCon 2019 ; Conference date: 11-04-2019 Through 14-04-2019",

year = "2019",

month = apr,

doi = "10.1109/SoutheastCon42311.2019.9020566",

language = "English",

series = "Conference Proceedings - IEEE SOUTHEASTCON",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 IEEE SoutheastCon, SoutheastCon 2019",

address = "United States",

}

El-Shahat, A, Ii, VF, Haddad, RJ & Ahad, M 2019, Optimal Power Cable for Smart Grids. in 2019 IEEE SoutheastCon, SoutheastCon 2019., 9020566, Conference Proceedings - IEEE SOUTHEASTCON, vol. 2019-April, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE SoutheastCon, SoutheastCon 2019, Huntsville, United States, 04/11/19. https://doi.org/10.1109/SoutheastCon42311.2019.9020566

TY - GEN

T1 - Optimal Power Cable for Smart Grids

AU - El-Shahat, Adel

AU - Ii, Vincent Faison

AU - Haddad, Rami J.

AU - Ahad, Mohammad

PY - 2019/4

Y1 - 2019/4

N2 - This paper investigates the calculation of ampacity values of medium voltage cable in an unfavorable burial method. The ampacity values are obtained using the International Electro-technical Commission (IEC) 60287 for all ac voltages with a 100% load factor in ducts, pipes, trenches. The cables are obtained from Leading Solution (LS) cable data sheet which provides the values for parameters needed to calculate the ampacity. The ampacity values are analyzed with constant and varying ambient temperature and burial depth. An Artificial Neural Network (ANN) is created to allow users to input a cables voltage and ampacity values in different situations to obtain an output of parameters for that specific cable. Ampacity value calculations showed an 8-15% difference from listed to those calculated. The regression factor of the ANN was around 0.996 and the overall error for all fourteen outputs was at maximum between 1-2%.

AB - This paper investigates the calculation of ampacity values of medium voltage cable in an unfavorable burial method. The ampacity values are obtained using the International Electro-technical Commission (IEC) 60287 for all ac voltages with a 100% load factor in ducts, pipes, trenches. The cables are obtained from Leading Solution (LS) cable data sheet which provides the values for parameters needed to calculate the ampacity. The ampacity values are analyzed with constant and varying ambient temperature and burial depth. An Artificial Neural Network (ANN) is created to allow users to input a cables voltage and ampacity values in different situations to obtain an output of parameters for that specific cable. Ampacity value calculations showed an 8-15% difference from listed to those calculated. The regression factor of the ANN was around 0.996 and the overall error for all fourteen outputs was at maximum between 1-2%.

KW - Ampacity

KW - Cables

KW - International Electro-technical Commission

KW - Medium voltage

KW - Neural Networks

UR - https://www.scopus.com/pages/publications/85082392032

U2 - 10.1109/SoutheastCon42311.2019.9020566

DO - 10.1109/SoutheastCon42311.2019.9020566

M3 - Conference article

AN - SCOPUS:85082392032

T3 - Conference Proceedings - IEEE SOUTHEASTCON

BT - 2019 IEEE SoutheastCon, SoutheastCon 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE SoutheastCon, SoutheastCon 2019

Y2 - 11 April 2019 through 14 April 2019

ER -

Optimal Power Cable for Smart Grids

Abstract

Publication series

Conference

UN SDGs

Scopus Subject Areas

Keywords

Access to Document

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