Abstract
The use of an internal digital communication network enhances the scalability, implementation and maintenance of Modular Multilevel Converters (MMC). However, it also introduces delays that limit the sampling frequency and the controller dynamic performance. In this paper, we propose a model-based predictor to compensate for the loop delay and overcome these limitations. Two benefits of this approach are possible: either designers can increase the sampling rate and control performance or employ a slower communication protocol/technology. In this paper, we present the mathematical description of the model-based predictor, assess the parameter sensitivity, and show matching simulation and experimental results that validate it. As constraints introduced by the use of digital communications are overcome, the results achieved encourage engineers to adopt a network into the design of Modular Multilevel Converters.
Highlights
Modular Multilevel Converters (MMCs) are built by series connections of identical modules
The number of cells in a converter depends on the nominal terminal voltage and the reliability requirements, with industrial MMCs reported in the literature in the medium, high, and extra high voltage levels [1,2]
The main contributions of this work are: adoption of a model-based predictor for compensating the additional latency introduced by the communication network; description of modulation and balancing schemes pertinent to network controlled MMCs and its relation to the proposed estimation algorithm; assessment of parameter variations in the control performance; and validation of the concept in an experimental set-up
Summary
Modular Multilevel Converters (MMCs) are built by series connections of identical modules (or cells). All the works listed addressed the former by adopting a ring topology (Figure 1) because it is the simplest one to offer two disjoint paths between any two nodes When it comes to performance, they used two non-exclusive strategies: to employ high bandwidth links with short forwarding delays and to reduce the communication payload. The main contributions of this work are: adoption of a model-based predictor for compensating the additional latency introduced by the communication network; description of modulation and balancing schemes pertinent to network controlled MMCs and its relation to the proposed estimation algorithm; assessment of parameter variations in the control performance; and validation of the concept in an experimental set-up.
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