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This paper presents an effective resonance suppression control for grid-interactive inverters with LCL filter in weak grid conditions. The resonance suppression mechanism is based on an adaptive model predictive control (AMPC). The large parasitic impedance and low SCR of weak grid challenges the operation of grid-interactive inverters. Specifically, the LCL filter resonance may get excited, resulting in collapse of the inverter operation. The proposed AMPC scheme autonomously alter the controller objectives for suppressing the resonance. The proposed control scheme alters the feedback currents based on the grid-condition. During the stiff grid conditions, grid current serves as feedback to the controller. While in the weak grid conditions, the inverter current is selected as feedback signal. The toggling action between these two feedback currents is determined by comparing moving RMS of grid current with desired current as constraint in the proposed AMPC cost function. The performance of proposed controller is verified experimentally. The results demonstrate that the proposed controller features robust performance under various grid conditions, model parameter mismatch, seamless transition between controller modes of operation and feedback alteration to attain resonance suppression, eliminates required tuning efforts in comparison to classical multi-nested loop control schemes, and provides high power quality.

This article proposes an optimal current control technique with switching event minimization for grid-interactive cascaded multilevel inverters (CMI) interfaced with battery energy storage sources. The proposed control scheme enables power-balancing functionality of battery cells, realizing optimal smart operation of CMI. Model predictive control (MPC) is known as a potential approach for multiobjective control schemes in single-loop manner for power electronics interfaces. However, MPC schemes are suffering from high computational burden that is magnified in topologies like the CMI, which have a substantial number of redundant control actions. The proposed control scheme utilizes a dynamic lookup matrix as an internal optimizer tool. The redundant switching sequences are cycled to equalize the power drawn from the independent battery energy storage sources while achieving a minimum energy control. The theoretical analysis and experimental case studies verify robustness and computational efficiency of the proposed multicriteria optimal controller with similar objective tracking when compared to finite-set MPC.