Adaptive fractional order control of doubly fed induction generator based wind energy conversion system under uncertainty

Conventional fossil fuel sources are being reduced and simultaneously became more and more sources of considerable undesirable influences on the environment. In an attempt to expand renewable energy sources, wind energy is playing a significant role. A doubly fed induction generator as an alternative concept of different prevalent generators in wind power industry has a conspicuous efficiency improvement impact. There are nonlinear dynamics and many uncertainties in wind power plants, such as matched and mismatched disturbances and uncertainties of parameters. Designing a convenient controller to address these nonlinearities and uncertainties is a problematic task and has been the topic of much great research. Sliding mode control is a powerful nonlinear high-frequency switching controller, which has been widely applied. In a more specialized scope, combining fractional order calculus with controllers provides more degrees of freedom for responding to the demands of existing fractional dynamics of systems. To this regard, this paper presents an adaptive fractional-order terminal sliding mode controller to extract maximum energy from a wind turbine based doubly fed induction generator, which as the name of the controller implies is adaptive and robust against uncertainties, improves control accuracy, reduces chattering and mechanical stresses, and speeds up response time. A novel and unique sliding surface has been selected for this controller. Lumped uncertainties and switching control signal parameters have been estimated by adaptation laws. Maximized aerodynamic wind energy has been harvested by utilizing the proposed controller for the rotor side converter. The Lyapunov theorem is applied to guarantee the closed-loop system stability. Under normal conditions and in the presence of uncertainty and disturbance, the proposed method has been compared with SMC and a feedback linearization proportional integral controller.

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