DocumentCode :
1893400
Title :
Electric load forecast for developing countries
Author :
Hamza, A. S Hafiz ; Abdel-Gawad, N.M. ; Salama, M.M. ; Hegazy, Ahmed ; El-Debeiky, S.
Author_Institution :
Shoubra Fac. of Eng., Zagazig Univ., Egypt
fYear :
2002
fDate :
2002
Firstpage :
429
Lastpage :
441
Abstract :
The electric utility planning process begins with the electric load forecasting, because of the advanced need for new utility plants. These long lead times require the utility planning horizon to be at least ten years long. Since utility decisions involve an economic analysis of the operating and investment costs, the utility planning horizon may range from fifteen to thirty years into the future. Forecasting load demand is a difficult procedure and combines art with science. The key contribution of forecasters is their knowledge of electricity consumers and an understanding of the way they use electricity and other competing energy forms. The problem gains special aspects in developing countries, such as Egypt, because of the high demand growth rate as well as the wide differences in the modes and levels of consumption in the various regions (governorates) in the country. In this study, several structures for neural networks are proposed and tested. They proved to perform as one of the best and most sophisticated load forecasting systems. In this study, the case of a number of neurons layers equal to 7 gives the best results with high accuracy with the least error. The forecasted peak loads and light loads, up to year 2010, for the six Regions of the Egyptian Unified Network; Alexandria, Delta, Cairo, North Upper Egypt, South Upper Egypt and the Canal, are obtained directly from one case by using actual and practical past ten years data.
Keywords :
electricity supply industry; load forecasting; neural nets; power system analysis computing; power system planning; Egypt; developing countries; economic analysis; electric load forecast; electric utility planning process; light loads; neural networks; neurons layers; peak loads; power system networks; Art; Costs; Economic forecasting; Energy consumption; Investments; Load forecasting; Neural networks; Power generation economics; Power industry; Process planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference, 2002. MELECON 2002. 11th Mediterranean
Print_ISBN :
0-7803-7527-0
Type :
conf
DOI :
10.1109/MELECON.2002.1014623
Filename :
1014623
Link To Document :
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