The residential electrical load in the city of Mosul as well as in most of cities in Iraq, is the major problem for the administration of electricity distribution. Since this kind of load is increasing drastically compared with other loads such as industrial, agricultural tourism and others which are declining for the last two decades due to unstable condition of the county. The residential electrical load components must be determined to solve the problems resulting from the significant increase in this load. This research aims to conduct a field survey to find out and identify the components of the residential electrical load ratios and qualitative change in the months of the year. The survey was conducted in the city of Mosul in northern Iraq. T he results were analyzed, and a number of recommendations were given to rationalize consumption.
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 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.