DocumentCode :
2466242
Title :
Electrical load forecasts in long-term and impact on load management application
Author :
Bendary, F. ; Mahmoud, Hanafy ; El-Sheikh, Salem
Author_Institution :
Fac. of Eng., Benha Univ., Shoubra, Egypt
fYear :
213
fDate :
10-13 June 213
Firstpage :
1
Lastpage :
4
Abstract :
The target of this paper is impacting Demand Side Management (DSM) when it is applied at different sectors; residential, commercial, public, government, agriculture, industrial and the total load of these sectors on national network of power system in Egypt for year (2009-2010) and estimating load forecast for these sectors by Adaptive Network Fuzzy Inference System (ANFIS) techniques during the period from year (2010-2011) to year (2020-2021).The daily load curve for maximum load of August month for year (2009-2010) as base year on Egyptian power system is expressed. Daily load forecast by using three techniques; Adaptive Network Fuzzy Inference System (ANFIS) technique, Artificial Neural Network (ANN) technique and Regression technique are estimated during period from year (2010-2011) to year (2020-2021), he is found the ANFIS technique is more suitable than other techniques. The daily load curve for maximum load of day from year (2009-2010) as base year on Egyptian power system is presented. Estimated daily load forecast by (ANFIS) technique during periodfrom year (2010-2011) to year (2020-2021)is shown.
Keywords :
demand side management; fuzzy reasoning; load forecasting; neural nets; power engineering computing; regression analysis; ANFIS technique; ANN technique; DSM; Egypt; Egyptian power system; adaptive network fuzzy inference system; artificial neural network; demand side management; electrical load forecasting; load curve; load management application; power system national network; regression technique;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Electricity Distribution (CIRED 2013), 22nd International Conference and Exhibition on
Conference_Location :
Stockholm
Electronic_ISBN :
978-1-84919-732-8
Type :
conf
DOI :
10.1049/cp.2013.0549
Filename :
6683152
Link To Document :
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