Fuzzy-C means clustering based ANFIS wind speed forecast

Abstract

Wind Energy is now becoming a widely used renewable source of energy for the restructured Power system operations around the world through Electric utilities. Unpredictability and instability of wind speed and wind power are the key problems with wind power generation. For solving the underlying problems, wind speed forecasting is essential. A lot of investigation has been going on over the last few years to predict wind speed with reduced prediction errors. This article introduces a new clustering approach based on a wind speed prediction based on the Adaptive-Neuro Fuzzy Inferencing Scheme (ANFIS). For the forecast, the original wind speed data for a month is used. The clustering is done with Fuzzy-C Means (FCM) algorithm. We like to specify that, we have taken user modified IEEE-30 Bus system for validation. The proposed FCM– ANFIS method proved to be better by comparing the Root Mean Square Error (RMSE) with the existing methods.