Forecasting and Modelling Electricity Demand Using Anfis Predictor
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.
DOI: https://doi.org/10.3844/jmssp.2011.275.281
Copyright: © 2011 M. Mordjaoui and B. Boudjema. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Electricity demand forecasting
- anfis system
- time series analysis
- appropriate parameterized
- final forecasting
- Principal Component Analysis (PCA)