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ANFIS Based Short Term Load Forecasting


Author : Harshad P. Oak and Shrikant J. Honade

Pages : 1878-1880
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Abstract

In recent years, load forecasting has become one of the major areas of research. Three kinds of forecasting can be performed depending on its occasion scale: short-, medium- and long-term. Short-term forecasts , in exacting have become even more important due to extensive rise of the spirited market. One of the most important benefits of the Short-term forecast is reliability for the system i.e. to make these savings reliable via optimal accurate forecasting. Artificial Neural Networks (ANNs) have been found useful in many non-linear applications employing knowledge-based techniques. This is mainly true for applications such as time-series examination. The success of applying ANN in time-series study has motivated a number of researchers to look at their use in solving the STF trouble. The adaptive neuro-fuzzy inference system presents a good option for the total and automatic parameter purpose for non-linear and real time scenarios.

Keywords: Short term load forecasting (STLF), adaptive neuro fuzzy inference system (ANFIS), neural network (NN).

Article published in International Journal of Current Engineering and Technology, Vol.5, No.3 (June-2015)

 

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