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The concept of smart grids has enabled the addition of renewable energy resources in the utility grids. This integration is possible after energy conversion and energy conversion causes the degradation in the quality of electric power. The power quality can be enhanced by reducing the total harmonic distortion (THD) in energy conversion. In this paper, we have presented an improved artificial neural network (ANN) based approach that can be useful to reduce the THD levels in a cascaded H-bridge (CHB) multilevel inverter (MLI). The proposed ANN architecture consists of only one hidden layer with ten neurons and can generate accurate results in both overfitting and underfitting conditions. Due to a smaller number of neurons, the proposed architecture is less complex and can produce results relatively faster as compared to other ANN architectures available in the literature. The proposed ANN architecture is …