M5P model tree based fast fuzzy maximum power point tracker

In spite of the many research contributions that have been introduced in the recent literature, maximum power point trackers (MPPT) still carry important issues related to convergence speed, computation load, accuracy, ease of implementation, and so on. The fuzzy logic based MPPT presents high steady-state performances in terms of speed of convergence and accuracy. However, the complexity of implementation is the first drawback of this MPPT type especially for embedded systems. In addition, fuzzy algorithms show relatively a large computation time compared to most of conventional MPPTs. In this way, the aim of this paper is to benefit from fuzzy logic advantages along with M5P model tree based modeling. Indeed, a new fast MPPT algorithm is established by modeling the fuzzy logic algorithm using M5P model tree that translates the model on simple if-then instructions. The new model has been trained based on simulation based dataset recorded for 500 W/m2 irradiation. The obtained model presents a good agreement with the fuzzy algorithm even for different irradiations and weather conditions. Furthermore, the developed algorithm shows improved performances compared to P&O and InCon algorithms. Moreover, satisfactory results have been obtained when the new algorithm has been subjected to one-day profile of real measurement.