Robust Model Predictive Rotor Current Control of a DFIG Connected to a Distorted and Unbalanced Grid Driven by a Direct Matrix Converter
| Autor: | Mauricio Aredes, Thiago Tricarico, Bruno W. Franca, Gustavo Gontijo, Emanuel L. van Emmerik, Leonardo Francisco da Silva |
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| Rok vydání: | 2019 |
| Předmět: |
Wind power
Renewable Energy Sustainability and the Environment Stator Rotor (electric) business.industry Computer science 020209 energy 020208 electrical & electronic engineering 02 engineering and technology Grid law.invention Model predictive control Reliability (semiconductor) law Control theory Control system 0202 electrical engineering electronic engineering information engineering Robust control business |
| Zdroj: | IEEE Transactions on Sustainable Energy. 10:1380-1392 |
| ISSN: | 1949-3037 1949-3029 |
| Popis: | The doubly fed induction generator (DFIG) has been widely used in the wind power industry due to its technical advantages. However, current research works aim at overcoming some of its drawbacks concerning reliability, efficiency, and power quality. Since the wind farms are usually located at remote places, connected to weak grids, high reliability is required and some power quality issues deserve attention. This paper proposes a low-complexity robust control of a DFIG driven by a direct matrix converter based on a model predictive rotor current control. The matrix converter is interesting due to the absence of the bulky and sensitive dc-link capacitors, leading to higher reliability. The predictive control is used to perform speed regulation. Moreover, this combination of a converter and straightforward control is proven to be a robust technique that naturally compensates for stator current issues, which arise due to a low-power-quality grid voltage. Besides, a linear model of the proposed system is presented in order to use the linear-control-theory tools to execute the system control design. A processor-in-the-loop simulation is employed to validate the proposed control. |
| Databáze: | OpenAIRE |
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