Process time and MPPT performance analysis of CF, LUT, and ANN control methods for a PMSG-based wind energy generation system

Authors: ABDULHAKİM KARAKAYA, ERCÜMENT KARAKAŞ

Abstract: Due to environmental issues such as global warming and the greenhouse effect, there is a growing interest in renewable sources of energy. Wind energy, which is the most important of these energy sources, can potentially meet a portion of the global energy demand. Numerous studies are being conducted worldwide to determine how the maximum level of power can be obtained from wind energy. In these studies, there is a particular interest in permanent magnet synchronous generators (PMSGs). This is because PMSGs exhibit a good performance within a wide range wind speeds and can be driven directly. In this study, the maximum power point tracking (MPPT) of a PMSG has been carried out by using a prototype built in a laboratory environment. The simulation model has been realized by utilizing MATLAB/Simulink and implemented by using dSPACE. MPPT has been performed by employing such control algorithms as an artificial neural network, a look-up table, and curve fitting in order to carry out comparative performance analyses of these control algorithms. Controllers were analyzed through comparisons between their MPPT and process performance. Based on our analysis results, we were able to identify controllers that were better in terms of power tracking and process performance.

Keywords: Maximum power point tracking, permanent magnet synchronous generator, artificial neural network, look-up table, curve fitting, wind energy

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