TY  - JOUR
AU  - Mordjaoui, M. 
AU  - Boudjema, B. 
PY  - 2011
TI  - Forecasting and Modelling Electricity Demand Using Anfis Predictor
JF  - Journal of Mathematics and Statistics
VL  - 7
IS  - 4
DO  - 10.3844/jmssp.2011.275.281
UR  - https://thescipub.com/abstract/jmssp.2011.275.281
AB  - 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.