Abstract
The present study focuses on distribution transformer load behavior and characteristics of residential consumers in Baghdad City. Real-data obtained from outputs of electrical load recording equipment and consumer billing data are used. The sample includes three categories of residential consumers from six different areas geographically distributed throughout the city (total of 3000 consumers). A novel algorithm called orthogonal particle swarm optimization is applied to construct a new approach to electricity demand modeling for the city. Then, the quantitative relationship between energy consumption, peak kW demand during peak demand periods (July and August), and annual energy consumption are evaluated. A quantitative relationship between the coincidence factor and N number of consumers is determined. Results of this study have been successfully applied in determining the distribution transformer burden, which can assist design engineers in calculating and setting the number of consumers connected to the distribution transformer. Such outcomes provide useful references for planning, designing, and load demand forecasting for power distribution systems in the future.
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