Abstract
This article presents a hierarchical finite-set model predictive control (MPC) scheme to enable autonomous operation and self-balancing cascaded multilevel inverter. The proposed approach is an alternative to MPC scheme based on a generic cost function, which in some applications is ill fit or challenging to design. The proposed controller has a hierarchical framework to eliminate the overall cost function optimization and associated weight factor design stage of the control objectives. The control formulation approach allows for multiobjective optimization with a cost-tolerance framework. The concept is well suited to simplify the control design stage of cascaded H-bridge inverters at the grid-edge with advanced functionality. The control scheme achieves active and reactive power control with switching event reduction while equalizing power draw from the independent voltage sources. The latter of these objectives is made possible by the proposed hierarchical approach to the control objective tracking. The control is modularized for each phase, making the system robust to unbalanced grid conditions. The concept is explained in depth in simulation, and then tested experimentally on hardware.
Highlights
M ULTILEVEL converters are a long-studied and widely accepted class of power converters
This article presented a new approach within the scope of finite-set model predictive control (MPC) framework for power electronic converters
Control objectives are ranked and given a cost tolerance, and switching sequences that do not meet the specified cost tolerance are removed from the optimization set of all the subsequent objectives
Summary
M ULTILEVEL converters are a long-studied and widely accepted class of power converters. The concept of an adaptive weight factor ratio for a power quality compensator was proposed in [26], where the weight factor of each control objective’s cost in the overall cost function adapts to the predicted optimal error of each term Still, such a control provides no guaranteed tracking performance of its objectives and requires normalizing its control objectives according to a predefined operating point. The control is modularized for each phase, making the CMI robust to unbalanced grid conditions It is beyond the scope of this article, the proposed control scheme can be integrated with energy management algorithms to optimize the power drawn from battery cells while considering current stresses on the battery cells during grid fast transients.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Journal of Emerging and Selected Topics in Power Electronics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
