The paper addresses an improved inner current reference calculation to be employed in the control of modular multilevel converters operating during either balanced or unbalanced conditions. The suggested reference calculation is derived based on the AC and DC additive and differential voltage components applied to the upper and lower arms of the converter. In addition, the impacts caused not only by the AC network's impedances but also by the MMC's arm impedances are also considered during the derivation of the AC additive current reference expressions. Another issue discussed in this article regards that singular voltage conditions, where the positive-sequence component is equal to the negative one, may occur not only in the AC network but also internally (within the converter's applied voltages). Several different inner current reference calculation methods are compared and their applicability during the former fault conditions is analyzed. The paper presents a detailed formulation of the inner current reference calculation and applies it to different unbalanced AC grid faults where it is shown that the presented approach can be potentially used to maintain the internal energy of the converter balanced during normal and fault conditions.
This paper focuses on the modeling, dynamic analysis, and simulation of the bidirectional DC-DC boost-buck power converter. The switching sequence applies different duty cycles in the input and output stages, resulting in full regulation of the system variables. By using this strategy, the input stage can be regulated disregarding perturbations in the output leg, as well as the output stage can be controlled independently of the effects of disturbances in the input part; which gives significant robustness to the converter. Based on the switching actions, the state-space average equations are derived, accomplishing the base to obtain the small-signal equations and equivalent small-signal circuits. The open-loop transfer functions are developed, besides the input and output impedance, and the audio susceptibility. Simulation results indicate that the proposed model can predict the dynamic behavior of the system in a wide range of the frequency spectrum, and the results in the time domain are in perfect agreement with the model predictions under disturbances of the control variables, variations of the value of the supply voltage and load changes.
The paper addresses a real-time optimization-based reference calculation integrated with a control structure for Modular Multilevel Converters (MMC) operating under normal and constrained situations (where it has reached current and/or voltage limitations, as it may occur during system faults). Firstly, a nonlinear optimization problem has been developed in which it prioritizes to satisfy the AC grid current set-points imposed by the transmission System Operator (TSO). The constrained nonlinear optimization problem is formulated based on the steady-state model of the MMC, whereby the prioritization is achieved through distinct weights defined in the Objective Function's (OF) terms. The resultant optimization problem, however, is highly nonlinear requiring high computation burden to be solved in real-time. To cope with this issue, this paper applies a Linear Time-Varying (LTV) approximation, which permits to represent the nonlinear dynamics of the system as constant parameters, while a Linear Time-Invariant (LTI) system is used to formulate the optimization constraints. The converter's current references are determined in real-time by solving a constrained linearized optimization problem at each control time step, which considers the TSO's demands, the current MMC operating point and its physical limitations. Theoretical analyses comparing the responses of the linear and nonlinear optimization problems are performed to validate the accuracy of the LTV approximation. Finally, the linearized-optimization problem is integrated with the MMC controllers, evaluated under different AC and DC network conditions and compared with conventional control strategies, where it is shown that the presented method can be potentially employed to obtain the MMC current references for distinct network scenarios.
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