Demand Forecasting Using Time Series Modelling and ANFIS Estimator

Author

Mohammadi, S. ; Keivani, H. ; Bakhshi, M. ; Mohammadi, A. ; Askari, M.R. ; Kavehnia, F.

Author_Institution

Islamic Azad Univ., Tehran

Volume

1

fYear

2006

fDate

6-8 Sept. 2006

Firstpage

333

Lastpage

337

Abstract

This paper provides an intelligence method for medium and long-term energy demand forecasting of a complicated electrical system. In this method we use energy data of several past years to train an adaptive network based on fuzzy inference system (ANFIS). We use this intelligence network to estimate the time series behaviour of energy consumption for several future years. Several simulations have been arranged to examine the efficiency of method.

Keywords

adaptive systems; fuzzy neural nets; fuzzy reasoning; learning (artificial intelligence); load forecasting; power system analysis computing; time series; ANFIS estimator; adaptive network training; adaptive neuro-fuzzy inference system; demand forecasting; energy consumption; intelligence network; load forecasting; time series modelling; Adaptive systems; Artificial neural networks; Demand forecasting; Economic forecasting; Load forecasting; Power system dynamics; Power system modeling; Power system planning; Power system security; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Universities Power Engineering Conference, 2006. UPEC '06. Proceedings of the 41st International

Conference_Location

Newcastle-upon-Tyne

Print_ISBN

978-186135-342-9

Type

conf

DOI

10.1109/UPEC.2006.367770

Filename

4218699