%0 Journal Article
	%A Mohamed Tarek Khadir and  Damien Fay and  Ahmed Boughrira
	%D 2008
	%J International Journal of Electrical and Computer Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 22, 2008
	%T Day Type Identification for Algerian Electricity Load using Kohonen Maps
	%U https://publications.waset.org/pdf/85
	%V 22
	%X Short term electricity demand forecasts are required
by power utilities for efficient operation of the power grid. In a
competitive market environment, suppliers and large consumers also
require short term forecasts in order to estimate their energy
requirements in advance. Electricity demand is influenced (among
other things) by the day of the week, the time of year and special
periods and/or days such as Ramadhan, all of which must be
identified prior to modelling. This identification, known as day-type
identification, must be included in the modelling stage either by
segmenting the data and modelling each day-type separately or by
including the day-type as an input. Day-type identification is the
main focus of this paper. A Kohonen map is employed to identify the
separate day-types in Algerian data.
	%P 3541 - 3545