NDLI: Power load forecasting using adaptive fuzzy inference neural networks

Content Provider	IEEE Xplore Digital Library
Author	Kodogiannis, V.S. Petrounias, I.
Copyright Year	2012
Description	Author affiliation: School of Electronics and Computer Science, University of Westminster, London, United Kingdom (Kodogiannis, V.S.) \|\| Manchester Business School, University of Manchester, Manchester, United Kingdom (Petrounias, I.)
Abstract	Load forecasting is a critical element of power system operation and planning, involving prediction of the future level of demand to serve as the basis for supply and demand planning. This includes planning for transmission and distribution facilities as well as new generation plants. This paper presents the development of a novel hybrid intelligent model and validates its prediction on the short-term electric load forecasting of the Power System of the Greek Island of Crete. The architecture and learning scheme of a novel fuzzy logic system (AFINN) implemented in the framework of a neural network is proposed. The network constructs its initial rules by clustering while the final fuzzy rule base is determined by competitive learning. The results corresponding to the minimum and maximum load time-series indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models.
Starting Page	238
Ending Page	243
File Size	319190
Page Count	6
File Format	PDF
ISBN	9781467322768
e-ISBN	9781467322782
DOI	10.1109/IS.2012.6335142
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-06
Publisher Place	Bulgaria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clustering algorithms Load modeling Load forecasting Neural networks Training Partitioning algorithms competitive learning Short-term load forecasting neurofuzzy systems clustering
Content Type	Text
Resource Type	Article

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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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