Efficiency maximization of grid-connected tidal stream turbine system: A supervisory energy-based speed control approach with processor in the loop experiment

Abstract

Permanent magnet synchronous generator (PMSG) with a back-to-back power converter is one of the commonly used technologies in tidal power generation schemes. However, the nonlinear dynamics and time-varying parameters of this kind of conversion system make the controller computation a challenging task. In the present paper, a novel intelligent control method based on the passivity concept with a simple structure is proposed. This proposed strategy consists of passivity-based speed control (PBSC) combined with a fuzzy logic method to address the robustness problems faced by conventional control techniques such as proportional-integral (PI) control. The proposed method extracts the maximum power from the tidal energy, compensates for the uncertainty in a damped way where the entire dynamics of the PMSG are considered when designing the control law. The fuzzy logic controller is selected, which makes the proposed strategy intelligent to compute the damping gains to make the closed-loop passive and approximate the unstructured dynamics of the PMSG. Thus, the robustness property of the closed-loop system is considerably increased. The regulation of DC voltage and reactive power to their desired values are the principal objectives of the present work. The proposed method is used to control the machine-side converter (MSC), while a conventional PI method is adopted to control the grid-side converter (GSC). Dynamic simulations show that the DC voltage and reactive power errors are extremely reduced with the proposed strategy; ±0.002 for the DC-link voltage and ±0.000015 in the case of the reactive power. Moreover, the lowest steady-state error and better convergence criterion are shown by the proposed control (0.3 × 10−3 s). Generally, the proposed candidate offers high robustness, fast speed convergence, and high efficiency over the other benchmark nonlinear strategies. Moreover, the proposed controller was also validated in a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad.