DocumentCode :
1183250
Title :
Long-Term Load Forecasting for Fast-Developing Utility Using a Knowledge-Based Expert System
Author :
Kandil, M. S. ; El-Debeiky, S. M. ; Hasanien, N. E.
Author_Institution :
Mansura University, Egypt; Ain Shams University, Egypt; Egyptian Electricity Authority, Egypt
Volume :
22
Issue :
4
fYear :
2002
fDate :
4/1/2002 12:00:00 AM
Firstpage :
78
Lastpage :
78
Abstract :
The application of the classical forecasting methods, when applied to a fast-developing utility with a period characterized by fast and dynamic changes, are insufficient and may provide an invaluable dimension to the decision-making process. In this paper, a knowledge-based expert system (ES) is implemented to support the choice of the most suitable load forecasting model for medium/long-term power system planning. In the proposed ES, the detailed problem statement including forecasting algorithms and the key variables (electrical and non-electrical variables) that affect the demand forecasts are first identified. A set of decision rules relating these variables are then obtained and stored in the knowledge base. Afterwards, the best model that will reflect accurately the typical system behavior over other models is suggested to produce the annual load forecast. A practical application is given to demonstrate the usefulness of the developed prototype system.
Keywords :
Costs; Distributed power generation; Expert systems; Load flow control; Load forecasting; Power system modeling; Predictive models; Steady-state; Turbines; Voltage control; Long-term load forecast; artificial neural network; expert systems; fast/normal developing utility; forecasting methods;
fLanguage :
English
Journal_Title :
Power Engineering Review, IEEE
Publisher :
ieee
ISSN :
0272-1724
Type :
jour
DOI :
10.1109/MPER.2002.4312144
Filename :
4312144
Link To Document :
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