Comparative Analysis of Artificial Intelligence-based MPPT Algorithms for Wind Energy System

Abstract

By extracting maximum possible power from a wind generator system, the efficiency of the system can be increased. Radial basis function (RBF), feed forward back propagation (FFBP) and adaptive neuro-fuzzy inference system (ANFIS) are recognized as the universal estimators. This paper presents a single network based maximum power point tracking (MPPT) of a wind turbine system using these algorithms. The single network based maximum power extraction method is simple and fast in maximum power point tracking. Moreover, it does not require any sensor or does not depend on system parameter measurements. The performance of the three different intelligent techniques are analyzed and compared. The simulation results demonstrate that while all the algorithms can track the maximum power point perfectly under continuously changing atmospheric condition with negligible error, the performance of RBF based technique is superior compared to the other two methods.