Multilevel Inverter with Predictive Control for Renewable Energy Smart Grid Applications

Abstract

In a world where climate changes and power management are becoming increasingly important, research work focuses on renewable energy based smart grid to meet adequate demands of energy. The smart grid is a modernized autonomous power network that can transmit electricity effectively, conserve resources and costs, and increase the local grid's stability. As a result, a smart grid connected multilevel inverter is presented in this work. The inverter is controlled using a model predictive control algorithm with increased levels with the primary goal of controlling the injected power generated by the renewable source, improving the quality of the current waveform, lowering THD, and eliminating the shift phase among the injected current and the grid voltage in effort to match the smart grid network's requirements. Therefore, this paper aims to show the performance analysis of multilevel inverters with predictive control for renewable energy smart grids application. The major concern was observed with most of the multi-level inverters are that with increased level total harmonic distortion (THD) is increased if switching control is not designed properly. Therefore, in this case predictive control is implemented on renewable energy based smart grid inverters to increase level with minimum voltage THD and current THD. The case analyzed voltage and current THD in the different levels of multilevel inverter. The result analysis was performed on 7, 11, 17, 21, 27, 31, 37 and 41 respectively. From result analysis it was observed that minimum THD was observed with level 31, i.e., 0.35% and at level 41 it was increased up to 0.55% which is still not high as compared to other existing MLI architectures. The result findings of proposed approach decreased THD with varying levels and outperforms better as compared to other works.