Research Article Open Access

Forecasting and Modelling Electricity Demand Using Anfis Predictor

M. Mordjaoui and B. Boudjema

Abstract

Problem statement: Load forecasting plays an important task in power system planning, operation and control. It has received an increasing attention over the years by academic researchers and practitioners. Control, security assessment, optimum planning of power production required a precise short term load forecasting. Approach: This study tries to combine neural network and fuzzy logic for next week electric load forecasting. The suitability of the proposed approach is illustrated through an application to electric load consumption data in 2010 downloaded from the RTE France website. Results: The study presents the results and evaluates them. Corresponding code was developed and used to forecast the next week load in a practical power system and the final forecasting result is perfect and consistent. Conclusion: The ANFIS system provides a useful and suitable tool especially for the load forecasting. The forecasting accuracy is high.

Journal of Mathematics and Statistics
Volume 7 No. 4, 2011, 275-281

DOI: https://doi.org/10.3844/jmssp.2011.275.281

Submitted On: 30 July 2011 Published On: 14 September 2011

How to Cite: Mordjaoui, M. & Boudjema, B. (2011). Forecasting and Modelling Electricity Demand Using Anfis Predictor. Journal of Mathematics and Statistics, 7(4), 275-281. https://doi.org/10.3844/jmssp.2011.275.281

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Keywords

  • Electricity demand forecasting
  • anfis system
  • time series analysis
  • appropriate parameterized
  • final forecasting
  • Principal Component Analysis (PCA)