The drastic increase of residential load consumption in recent years result in over loading feeder lines and transformers for the Iraqi northern area distribution system especially in the city of Mosul. Solution for this problem require up to date research study consumers load to find the proper solution to stop excess overload in the transformers and the feeders. This paper include the regional survey for samples of consumers representing typical types of different standard of living and energy consumption by distributing questioners contain list of information such as load type in daily use. Also current readings are recorded for the individual consumer for the months of the year 2006. In addition to those readings, energy consumption is recorded once every two months. The registered readings are used in conjunction with the list of questioners to find a sample (for different loads) that coincide with the list of questioner for current and energy readings. Resulting in the feasibility of using the sample to know the peak value of current for any consumer not included in the list of questioner and for any new consumer, since it become possible to decide the size of the transformers and feeder lines, to overcome the problem of overloading in any part of the distribution system. The Artificial Neural Network (ANN) is used in this paper to find the above mentioned sample.
| Published in | American Journal of Electrical Power and Energy Systems (Volume 2, Issue 5) |
| DOI | 10.11648/j.epes.20130205.11 |
| Page(s) | 111-115 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2013. Published by Science Publishing Group |
Consumer Peak Load, ANN, Distribution System, Iraqi Distribution Network
| [1] | J. Nazarko, R. P. Broadwater & N. I. Tawalbeh "Identification of statistical properties of diversity and conversion factors from load research data" Electro technical Conference, 1998. MELECON 98., 9th Mediterranean Volume 1, Issue , 18-20 May 1998, vol.1, PP 217 – 220. |
| [2] | A. Sargent, R. P. Broadwater, J.C. Thompson & J. Nazarko " Estimation of diversity and KWHR-to-peak-KW factors from load research data" IEEE Transactions on Power Systems, Volume 9, Issue 3, Aug 1994 PP 1450 – 1456. |
| [3] | J. Hertz, A. Krough & R. Palmer, "Introduction to the Theory of Neural Computation." Addison – Wesley, 1991. |
| [4] | P.D. Wassermann, " Neural Computing: Theory and Practice." New York, Van Nostrand Reinhold, 1989. |
| [5] | Warwick, A. Ekwue & R. Aggarwal "Artificial intelligence techniques in power systems" IEE Power Engineering Series 22, London, 1997l |
APA Style
M. A. Al-Nama, M. S. Al-Hafid, A. S. Al-Fahadi. (2013). Estimation of the Consumer Peak Load for the Iraqi Distribution System Using Intelligent Methods. American Journal of Electrical Power and Energy Systems, 2(5), 111-115. https://doi.org/10.11648/j.epes.20130205.11
ACS Style
M. A. Al-Nama; M. S. Al-Hafid; A. S. Al-Fahadi. Estimation of the Consumer Peak Load for the Iraqi Distribution System Using Intelligent Methods. Am. J. Electr. Power Energy Syst. 2013, 2(5), 111-115. doi: 10.11648/j.epes.20130205.11
AMA Style
M. A. Al-Nama, M. S. Al-Hafid, A. S. Al-Fahadi. Estimation of the Consumer Peak Load for the Iraqi Distribution System Using Intelligent Methods. Am J Electr Power Energy Syst. 2013;2(5):111-115. doi: 10.11648/j.epes.20130205.11
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author = {M. A. Al-Nama and M. S. Al-Hafid and A. S. Al-Fahadi},
title = {Estimation of the Consumer Peak Load for the Iraqi Distribution System Using Intelligent Methods},
journal = {American Journal of Electrical Power and Energy Systems},
volume = {2},
number = {5},
pages = {111-115},
doi = {10.11648/j.epes.20130205.11},
url = {https://doi.org/10.11648/j.epes.20130205.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20130205.11},
abstract = {The drastic increase of residential load consumption in recent years result in over loading feeder lines and transformers for the Iraqi northern area distribution system especially in the city of Mosul. Solution for this problem require up to date research study consumers load to find the proper solution to stop excess overload in the transformers and the feeders. This paper include the regional survey for samples of consumers representing typical types of different standard of living and energy consumption by distributing questioners contain list of information such as load type in daily use. Also current readings are recorded for the individual consumer for the months of the year 2006. In addition to those readings, energy consumption is recorded once every two months. The registered readings are used in conjunction with the list of questioners to find a sample (for different loads) that coincide with the list of questioner for current and energy readings. Resulting in the feasibility of using the sample to know the peak value of current for any consumer not included in the list of questioner and for any new consumer, since it become possible to decide the size of the transformers and feeder lines, to overcome the problem of overloading in any part of the distribution system. The Artificial Neural Network (ANN) is used in this paper to find the above mentioned sample.},
year = {2013}
}
TY - JOUR T1 - Estimation of the Consumer Peak Load for the Iraqi Distribution System Using Intelligent Methods AU - M. A. Al-Nama AU - M. S. Al-Hafid AU - A. S. Al-Fahadi Y1 - 2013/08/20 PY - 2013 N1 - https://doi.org/10.11648/j.epes.20130205.11 DO - 10.11648/j.epes.20130205.11 T2 - American Journal of Electrical Power and Energy Systems JF - American Journal of Electrical Power and Energy Systems JO - American Journal of Electrical Power and Energy Systems SP - 111 EP - 115 PB - Science Publishing Group SN - 2326-9200 UR - https://doi.org/10.11648/j.epes.20130205.11 AB - The drastic increase of residential load consumption in recent years result in over loading feeder lines and transformers for the Iraqi northern area distribution system especially in the city of Mosul. Solution for this problem require up to date research study consumers load to find the proper solution to stop excess overload in the transformers and the feeders. This paper include the regional survey for samples of consumers representing typical types of different standard of living and energy consumption by distributing questioners contain list of information such as load type in daily use. Also current readings are recorded for the individual consumer for the months of the year 2006. In addition to those readings, energy consumption is recorded once every two months. The registered readings are used in conjunction with the list of questioners to find a sample (for different loads) that coincide with the list of questioner for current and energy readings. Resulting in the feasibility of using the sample to know the peak value of current for any consumer not included in the list of questioner and for any new consumer, since it become possible to decide the size of the transformers and feeder lines, to overcome the problem of overloading in any part of the distribution system. The Artificial Neural Network (ANN) is used in this paper to find the above mentioned sample. VL - 2 IS - 5 ER -
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