Resumen
Commonly, electrical energy is generated by using non-renewable energy such as natural gas, coal, and oil. As electrical energy is a basic asset for the development of a region, its utilization is increasing every year, which causes the existence of non-renewable energy to decrease every year. This issue is becoming a serious concern all over the world, which encourages every country to harness energy from renewable energy. Wind energy is a promising candidate for generating electricity today. In wind turbine generation, a three-phase generator is usually used. Along with the rapid development of power electronic devices and efforts to improve generator performances, the use of a multiphase system is considered important for harnessing energy from the wind more efficiently. In this study, a five-phase system is proposed to upgrade the output power and power density of the most qualified AFPMG in the previous study. The Taguchi optimization method is employed to obtain the lowest total harmonic distortion (THD) of the on-load voltage waveform. In addition to the Taguchi method, an Artificial Neural Network (ANN) is also employed to compare the results from the Taguchi method and the results are proven to have an excellent relationship. The data processed for Taguchi and ANN methods are strongly helped by using the finite element method from the Ansys Maxwell software. The performances of the proposed five-phase axial flux permanent magnet generator (FP-AFPMG) show good improvement, especially in THD, ripple torque, and ripple in the rectified voltage.