Wind turbine torque-speed feature emulator using a DC motor

Taveiros, Filipe Emanuel Vieira; Barros, Luciano Sales

doi:10.1109/cobep.2013.6785159

Cited by 11 publications

(2 citation statements)

References 9 publications

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“…Theoretically, a maximum of 59.3% of the wind power can be harnessed and converted by a turbine. However, actual turbines have maximum power coefficient around 35e45% [24,25]. As stated in (1), the power coefficient is a parcel of the TSR and the pitch angle, which means that the harnessing of the turbine can be controlled by means of l and b.…”

Section: Power Controlmentioning

confidence: 99%

Back-to-back converter state-feedback control of DFIG (doubly-fed induction generator)-based wind turbines

Taveiros

Barros

Costa

2015

Energy

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Section: Power Controlmentioning

confidence: 99%

Back-to-back converter state-feedback control of DFIG (doubly-fed induction generator)-based wind turbines

Taveiros

Barros

Costa

2015

Energy

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“…A detailed literature review has shown that several researchers have utilized different motor types, such as separately excited dc motors, Permanent Magnet Synchronous Motor (PMSM), squirrel cage induction motors, and servomotors, etc. Furthermore, it has been noted that in the past, researchers often developed WTE based on a dc motor [6], [9], [10], [11], [12], [13], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40] with current control (i.e. torque control on its shaft).…”

Section: Introductionmentioning

confidence: 99%

An Experimental Hybrid Control Approach for Wind Turbine Emulator

et al. 2023

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In this study, the experimental implementation of a Hybrid Controller (HC) for a Wind Turbine Emulator (WTE) is presented. Conventionally, the speed control of a WTE is based on two Proportional Integral (PI) controllers used for the outer (speed) loop and inner (torque) loop of a DC motor drive. However, based on the extensive literature survey, with the PI controllers alone, significant overshoot and substantial settling time in the speed response are unavoidable. The overshoot cannot be completely removed without sacrificing speediness. To eliminate the overshoot and concurrently improve the settling time, an HC, combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and PI controller for the outer and inner loops, respectively, is proposed, designed, implemented and analyzed. The actual wind turbine is emulated using a 2-quadrant DC motor drive based on DS1104 R&D controller board from dSPACE. These two control schemes, namely PI (both controllers are PI), and HC (PI controller for inner loop and ANFIS controller for outer loop) for the WTE are extensively simulated based on the small-scale wind turbine model and eventually implemented using a small-scale laboratory set-up. When implemented in the WTE, with a step-change in wind speed, the hybrid control scheme produces a better result. It is found out the Root Mean Square Error (RMSE) for the WTE rotor speed of the HC is 0.495, which is lower compared to PI control scheme RMSE of 0.7273. Finally, to verify the validity of the WTE based on HC, a random wind speed with wind turbine parameters extracted from the actual wind turbine is applied. The results indicated that the WTE perfectly emulated the wind turbine rotor speed with an RMSE of 0.5004. INDEX TERMSWind turbine emulator (WTE), ANFIS controller, PI controller, DS 1104 R&D Controller Board, wind energy conversion system (WECS), hybrid controller.

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Heightened state-feedback predictive control for DFIG-based wind turbines to enhance its LVRT performance

Taveiros

Barros

2019

International Journal of Electrical Power & Energy Systems

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Wind turbine torque-speed feature emulator using a DC motor

Cited by 11 publications

References 9 publications

Back-to-back converter state-feedback control of DFIG (doubly-fed induction generator)-based wind turbines

Back-to-back converter state-feedback control of DFIG (doubly-fed induction generator)-based wind turbines

An Experimental Hybrid Control Approach for Wind Turbine Emulator

Heightened state-feedback predictive control for DFIG-based wind turbines to enhance its LVRT performance

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