DocumentCode
545623
Title
Estimation of the consumer peak load for the Iraqi distribution system using intelligent methods
Author
Al-Nama, M.A. ; Al-Hafid, M.S. ; Al-Fahadi, A.S.
Author_Institution
Dept. of Comput. Eng., Al-Hadbaa Univ., Iraq
fYear
2010
fDate
Nov. 30 2010-Dec. 2 2010
Firstpage
374
Lastpage
378
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 requires up to date research consumers load study 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 questionnaires to find a sample (for different loads) that coincide with the list of questionnaires for current and energy readings. Resulting in the feasibility of using the sample to know the peak value of current for any consumer even if he is not included in the list of questionnaires 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.
Keywords
distribution networks; neural nets; power system analysis computing; power transformers; artificial neural network; consumer peak load; distribution system; energy consumption; feeder lines; intelligent methods; power transformers; residential load consumption; Accuracy; Artificial intelligence; Artificial neural networks; Energy consumption; Estimation; Training; Water heating; ANN; Consumer Peak Load; Distribution System;
fLanguage
English
Publisher
ieee
Conference_Titel
Energy, Power and Control (EPC-IQ), 2010 1st International Conference on
Conference_Location
Basrah
Electronic_ISBN
978-0-9568330-0-6
Type
conf
Filename
5767344
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