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Model predictive control is identified as one of the emerging control platforms which can replace the classical linear as well as sliding mode controls of power converters and drives. Implementing this algorithm in grid tied converter control imposes its design parameters like sampling frequency, cost function coefficients, model parameters etc. to be aptly chosen to match with hardware intricacies. Therefore, a detailed investigation for the interoperability of various MPC design parameters and the relative performance across each case is felt necessary. This paper presents one such primary investigation carried out in the pre-experimentation stage to identify the correlation between sampling rates of model predictive control for desired performance indices like tracking accuracy, average inverter switching frequency, current harmonic profile and inverter power loss applied to a three phase grid connected inverter. While implementing the control, a discrete time model representing a 15kW grid tied inverter is developed for current prediction followed by a suitable cost function formulation aimed at accurate reference tracking. From the analysis, it is observed that the tracking accuracy greatly depends on the prediction interval, which in turn depends on the sampling rates. The inverter is tested for its dynamic performance by considering step change in reference and source specifications besides steady state analysis. Extensive analysis for various combinations of MPC design parameters and their relative performance merits on the inverter output is presented. The results exhibited high reference tracking accuracy with improved harmonic profile for high to moderate sampling frequencies, but with a tax on the inverter efficiency. The choice of switching frequency for a trade-off between high tracking accuracy and inverter efficiency is also suggested.

Performance Evaluation of Model Predictive Current Controlled Grid Tied Converter for Sampling Frequency Variations