Title :
Peak load estimation in distribution networks by fuzzy regression approach
Author :
G. Cartina;V. Alexandrescu;G. Grigoras;M. Moshe
Author_Institution :
Tech. Univ. of Iasi, Romania
Abstract :
One of the first steps in distribution networks development planning is to forecast the loads, loads that the networks will supply. The load estimation used in electrical networks planning must consider not only the future loads, but also their geographical positions, for permitting the designer to locate and to dimension the electrical equipment. The load estimation influences various aspects of distribution system planning such as peak load demand period, transformer sizing, conductor sizing, capacitor placement, and so on. Hence, the peak load estimation is a problem of a special interest. The most efficient method in estimation of the peak load consists in utilization of the periodic energy consumption by customers who are divided into classes having different load shapes. In the first section of this work an analysis of the estimation methods for the peak load is presented. In the next sections a new method based on nonlinear fuzzy regression is described. The choice of the method depends on available data, the imposed goal and accuracy.
Keywords :
"Intelligent networks","Energy consumption","Shape","Substations","Oil insulation","Conductors","Capacitors","Power system management","State estimation","Power system planning"
Conference_Titel :
Electrotechnical Conference, 2000. MELECON 2000. 10th Mediterranean
Print_ISBN :
0-7803-6290-X
DOI :
10.1109/MELCON.2000.879679