A Neuro-fuzzy Approach for Predicting Load Peak Profile

Abdellah Draidi, Djamel Labed


Load forecasting has many applications for power systems, including energy purchasing and generation, load switching, contract evaluation, and infrastructure development.

Load forecasting is a complex mathematical process characterized by random data and a multitude of input variables.To solve load forecasting, two different approaches are used, the traditional and the intelligent one.Intelligent systems have proved their efficiency in load forecasting domain.

Adaptive neuro-fuzzy inference systems (ANFIS) are a combination of two intelligent techniques where we can get neural networks and fuzzy logics advantages simultaneously.

In this paper, we will forecast night load peak of Algerian power system using multivariate input adaptive neuro-fuzzy inference system (ANFIS) introducing the effect of the temperature and type of the day as input variables.


Load forecasting; Algerian power systems; neuro-fuzzy network; temperature; type of the day.

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DOI: http://doi.org/10.11591/ijece.v5i6.pp1304-1310

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).