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This paper presents a method for the control design of five-level DCC converters based on mixed-integer optimization and machine learning. The resulting controller is computationally simple and can be easily implemented on low-resource control hardware using simple nested "if-else" statements. The optimization problem is recalled from previous work by modifying the cost function to further enhance the dynamic performance. Additionally, and in contrast to previous works, the online implementation accomplished in this paper allows the system to cover a wider range of operating points. For this, the optimization problem is solved offline for several operating conditions, and the results are gathered into a dataset to train classification and regression trees (CARTs), which are later used online. Due to the generalization capability of the CARTs, a more flexible and less resource-intensive implementation is achieved which is capable of operating at points outside the ones considered in the training dataset. The resulting control strategy is compared in simulation and experiments with several alternative approaches found in the literature. This approach can be extended to other power converter topologies, allowing the implementation of optimized modulations. • Modulation of five-level DCC as a mixed-integer optimization problem. • Achievement of wider range of operating points. • Classification and regression trees used for implementation of optimization problem. • Guidelines for robust implementation of such tress. • In-detail comparison with existing approaches both in simulation and experiments. [ABSTRACT FROM AUTHOR]

Multilevel converters are nowadays an enabling key in the integration of electric power into the grid as they introduce less distortion and, thus, they are more compliant with the grid standards, among other benefits. A well-known topology is the three-level Neutral-Point-Clamped whose control requires to deal with the capacitors voltage unbalance. This paper presents a modulation approach where the injection of a common component in the modulated voltage is studied in order to achieve such voltage balance. An optimization problem that, apart from the voltage balance, aims the lowest number of commutations and can be solved very efficiently with up to five computations of the cost function is formulated. The main advantages of the proposed modulation strategy are its simplicity and its flexibility, since it is also valid for unbalanced grid conditions and, with little added complexity, for low (and even zero) power factor conditions. Simulation results under unbalanced grid conditions are provided in order to show its validity under this scenario. The strategy is evaluated and compared with a space-vector-based approach in an experimental setup, yielding similar total harmonic current distortion, a 30% reduction in the number of commutations, and better voltage balance performance for lower power factor conditions. • A modulation approach for capacitors balance in NPC converters is proposed. • The advantages are simplicity and validity for unbalanced-grid-voltage conditions. • The number of commutations is optimized. • An enhancement is proposed to work under low-power-factor conditions. • Experimental comparison with virtual space vector is performed. [ABSTRACT FROM AUTHOR]