Paper Information

Journal:   JOURNAL OF ARTIFICIAL INTELLIGENCE IN ELECTRICAL ENGINEERING   SEPTEMBER 2014 , Volume 3 , Number 10; Page(s) 37 To 50.
 
Paper: 

NEURAL NETWORKS IN ELECTRIC LOAD FORECASTING: A COMPREHENSIVE SURVEY

 
 
Author(s):  MANSOURI VAHID*, AKBARI MOHAMMAD E.
 
* DEPARTMENT OF ELECTRICAL ENGINEERING, AHAR BRANCH, ISLAMIC AZAD UNIVERSITY, AHAR, IRAN
 
Abstract: 

Review and classification of electric load forecasting (LF) techniques based on artificial neural networks (ANN) is presented. A basic ANNs architectures used in LF reviewed. A wide range of ANN oriented applications for forecasting are given in the literature. These are classified into five groups: (1) ANNs in short-term LF, (2) ANNs in mid-term LF, (3) ANNs in long-term LF, (4) Hybrid ANNs in LF, (5) ANNs in Special applications of LF. The major research articles for each category are briefly described and the related literature reviewed. Conclusions are made on future research directions.

 
Keyword(s): ARTIFICIAL NEURAL NETWORKS (ANNS), LOAD FORECASTING (LF), SHORT TERM LF, MID TERM LF, LONG TERM LF, PEAK LF, UNIT COMMITMENT (UC)
 
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