NDLI: Monthly Electric Energy Demand Forecasting Based on Trend Extraction

Content Provider	IEEE Xplore Digital Library
Author	Gonzalez-Romera, E. Jaramillo-Moran, M.A. Carmona-Fernandez, D.
Copyright Year	1969
Abstract	Medium-term electric energy demand forecasting is an essential tool for power system planning and operation, mainly in those countries whose power systems operate in a deregulated environment. This paper proposes a novel approach to monthly electric energy demand time series forecasting, in which it is split into two new series: the trend and the fluctuation around it. Then two neural networks are trained to forecast them separately. These predictions are added up to obtain an overall forecasting. Several methods have been tested to find out which of them provides the best performance in the trend extraction. The proposed technique has been applied to the Spanish peninsular monthly electric consumption. The results obtained are better than those reached when only one neural network was used to forecast the original consumption series and also than those obtained with the ARIMA method
Sponsorship	IEEE Power Engineering Society
Starting Page	1946
Ending Page	1953
Page Count	8
File Size	448748
File Format	PDF
ISSN	08858950
Volume Number	21
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Demand forecasting Economic forecasting Load forecasting Neural networks Power system planning Weather forecasting Hybrid power systems Artificial neural networks Job shop scheduling Power system management time series neural network applications power system planning
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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