DocumentCode
3624665
Title
Preliminary comparison of different neural-fuzzy mappers for load curve short term prediction
Author
Dzenana Malkocevic;Tatjana Konjic;Vladimiro Miranda
Author_Institution
Elektroprivreda BiH, TEMPUS CEFES post-graduation program run, Universities of Tuzla (BiH), Novi Sad (Serbia) and Skopje (FYR of Macedonia). m.dzenana@gmail.com
fYear
2006
Firstpage
213
Lastpage
217
Abstract
This paper is written with the didactic purpose of exploring and indicating possibilities to power companies in the Balkan region for the application of adaptive neuro-fuzzy inference system (ANFIS) models in load prediction with real load data set. ANFIS models were trained and tested using 15-minute load data collected in Portugal by the electric power company EDP during a 42 day period. Simulation results gave promising results especially considering small size of used data set. Although the objective of the paper is to demonstrate possibilities for practical implementation, further research and improvement including the contributions of similar approaches in the world must be done
Keywords
"Power system modeling","Load forecasting","Power system dynamics","Adaptive systems","Predictive models","Power system control","Power system planning","Neural networks","Fuzzy systems","Power systems"
Publisher
ieee
Conference_Titel
Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on
Print_ISBN
1-4244-0432-0
Type
conf
DOI
10.1109/NEUREL.2006.341216
Filename
4147204
Link To Document