A STLF in distribution systems - A short comparative study between ANFIS Neuro-Fuzzy and ANN approaches - part II

Author

Rafael, S. ; Santos, P. ; Lobato, P. ; Pires, A.J.

Author_Institution

Dept. of Electr. Eng. at ESTSetubal, Polytech. Inst. of Setubal, Sebutal

fYear

2009

fDate

18-20 March 2009

Firstpage

666

Lastpage

669

Abstract

This paper present a comparative study between ANFIS, neuro-fuzzy (NF) and artificial neural network (ANN) approaches, applied to STLF algorithm (one hour ahead). Distribution networks need reliable short-term load forecast. The STLF algorithms associated with network management, as load dispatch and network reconfiguration, under quality of service constraints, improves the maintenance issues and eventual power purchase decisions within liberalized electricity markets.

Keywords

distribution networks; fuzzy set theory; load dispatching; load forecasting; neural nets; power engineering computing; power markets; power system management; quality of service; artificial neural network approaches; distribution networks; distribution systems; load dispatching; markets; network management; neuro-fuzzy approach; power purchase decisions; quality of service constraints; short-term load forecast; Artificial neural networks; Electricity supply industry; Energy management; Load forecasting; Load management; Maintenance; Noise measurement; Power system reliability; Quality management; Quality of service; Artificial neural network; Consumption trend; Electrical distribution network; Neuro-fuzzy; Short-term load forecast;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering, Energy and Electrical Drives, 2009. POWERENG '09. International Conference on

Conference_Location

Lisbon

Print_ISBN

978-1-4244-4611-7

Electronic_ISBN

978-1-4244-2291-3

Type

conf

DOI

10.1109/POWERENG.2009.4915183

Filename

4915183