Paper Information

Title: 

THE LONG TERM FORCAST OF ELECTRIC ENERGY DEMAND IN AZARBAIJAN USING NEURAL NETWORK

Type: PAPER
Author(s): KHANKESHIZADE MOHARRAM*
 
 *AZARBAIJAN POWER ENGINEERING CONSULTANTS CO.(MONA), TABRIZ, IRAN
 
Name of Seminar: INTERNATIONAL POWER SYSTEM CONFRENCE
Type of Seminar:  CONFERENCE
Sponsor:  SHERKATE TAVANIR
Date:  2004Volume 19
 
 
Abstract: 

THE PREDICTION OF ELECTRIC ENERGY DEMAND IS ONE OF THE MAIN FUNCTIONS OF THE ENERGY MANAGEMENT SYSTEMS (EMS). IN THE PRESENT PAPER WITH RESPECT TO SIGNIFICANCE OF THE SUBJECT , RECURRENT MULTILAYER PERCEPTRON NEURAL NETWORK KNOWN AS RMLP NETWORK, HAS BEEN USED FOR THE LONG TERM FORECASTING OF THE ELECTRIC ENERGY DEMAND IN AZARBAIJAN AREA. AS FOR THE NETWORK TRAINING, A PART FROM THE EXPLANATORY VARIABLES AFFECTING THE ELECTRIC ENERGY USAGE SYSTEM, SUM ELEMENTS OF THE ENERGY BALANCE OF THE AREA HAS ALSO BEEN PUT IN TO USE. FROM 1369 TO 1380 AND FROM 1381 TO 1390 HAVE RESPECTIVELY BEEN CHOSEN FOR THE PERIOD OF THE BASE OF THE FORCAST AND FORCAST PERIOD. IN THE END, THE OBTAINED RESULTS HAVE BEEN COMPARED WITH RESULTS ACHIEVED BY A CONVENTIONAL MATHEMATICAL METHOD AND ACTUAL ELECTRIC ENERGY DEMAND IN THE AREA.

 
Keyword(s): FORECASTING, ENERGY DEMAND, ENERGY BALANCE, NEURAL NETWORK
 
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