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Modelling and Simulation of Artificial Neural Network Based Harmonic Elimination Technique for Solar-Fed Cascaded Multilevel Inverter
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Abstract
This paper presents the harmonic elimination technique for a fifteen level cascaded multilevel inverter (CMLI) supplied with the seven varying DC input sources. Here, the input supply sources are obtained from the solar Photovoltaic’s (PV). The harmonic equations are solved and switching angles are obtained in such a way that the fundamental is kept constant and lower order harmonics are minimized or eliminated. The data set with varying input DC voltages and switching angles are trained with Artificial Neural Network (ANN). This trained network is integrated with CMLI to improve the power quality. The modeling of solar panel which serves as the input to the CMLI is developed. A eleven level CMLI with five varying DC input sources and a set of multiple carrier Pulse Width Modulation (PWM) methods are also given for comparison. The results show that ANN based method provides a significant improvement with respect to the reduction of Total Harmonic Distortion (THD).
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References
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