DocumentCode :
2504425
Title :
A hybrid expert system assisting decision making for distribution system load forecasting
Author :
Morsi, D.M. ; Abbasy, N.H. ; Ella, M. S Abul
Author_Institution :
Dept. of Electr. Eng., Alexandria Univ., Egypt
fYear :
1994
fDate :
12-14 Apr 1994
Firstpage :
893
Abstract :
This paper introduces a typically intelligent hybrid expert system (ES) for an annualized distribution system load forecasting. The proposed ES has the capability of predicting the annual distribution substation load growth, and patterns of subsequent load shifts, in the case of a substation overload. Also, possible expected system expansion plans are introduced. The parameters of the load growth model are estimated for each substation. The load transfer model is chosen to follow the Weibull distribution function and to simulate different factors affecting the transfer process. The ES is developed using an artificial intelligence language (PROLOG), and is applied to Alexandria city, 66/11 kV power distribution network
Keywords :
Weibull distribution; decision support systems; digital simulation; distribution networks; expert systems; load forecasting; power system analysis computing; power system planning; substations; 11 kV; 66 kV; Alexandria city; PROLOG; Weibull distribution function; annual distribution substation load growth; artificial intelligence language; decision making; distribution system; expected system expansion plans; hybrid expert system; intelligent hybrid expert system; load forecasting; load growth model estimation; load shift patterns; load transfer model; transfer process; Artificial intelligence; Cities and towns; Decision making; Expert systems; Hybrid intelligent systems; Load forecasting; Load modeling; Power system modeling; Substations; Weibull distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference, 1994. Proceedings., 7th Mediterranean
Conference_Location :
Antalya
Print_ISBN :
0-7803-1772-6
Type :
conf
DOI :
10.1109/MELCON.1994.380958
Filename :
380958
Link To Document :
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