Slidingmode control of induction generator wind turbine connected to the grid

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Abstract

Conventional fossil fuels such as coal, oil and natural gas are being reduced and become more and more a source of serious undesirable effects on the environment. Wind power is playing a major role in the effort to augment the share of renewable energy sources in the world energy mix with a continuously increasing penetration into the grid. Wind turbine generators can be divided into two basic categories: fixed speed and variable speed. Variable-speed wind energy systems are presently favored than fixed-speed wind turbines thanks to their higher wind power extraction, improved efficiency, reactive power support and voltage control. This study addresses the problem of control of Wind Energy Conversion System (WECS) in variable speed. To this end, two simultaneous control objectives, namely the maximization of the energy conversion efficiency based on Squirrel Cage Induction Generator (SCIG) wind turbine and the regulation of the active and reactive power feed to the grid, to guarantee Unit Power Factor (UPF), have been established. To deal with the complexity and nonlinearity of the system, the sliding mode control is adopted. Indeed, this technique provides an efficient tool for controller design and presents attractive features such as robustness to parametric uncertainties of the different components of the system. In this way, sliding-mode control laws are developed using Lyapunov stability analysis, to guarantee the reaching and sustaining of sliding mode and stability of the system control. Evaluation of the reliability and performance of the proposed sliding mode control approach has been established on a 3MW three-blade wind turbine. Simulation results demonstrate that the proposed control strategy is effective in terms of MPPT control strategy, active and reactive power tracking trajectories and robustness against system parameter variations.

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Ouassaid, M., Elyaalaoui, K., & Cherkaoui, M. (2016). Slidingmode control of induction generator wind turbine connected to the grid. In Studies in Computational Intelligence (Vol. 635, pp. 531–553). Springer Verlag. https://doi.org/10.1007/978-3-319-30169-3_23

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