On Wind Turbine Power Delta Control

Elorza, Iker; Calleja, Carlos; Pujana-Arrese, Aron

doi:10.3390/en12122344

Cited by 10 publications

(9 citation statements)

References 22 publications

(54 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Equations (11) and (12) show that the stator active power is controlled with the q component of the rotor current and the stator reactive power with the rotor current d component.…”

Section: Dfig Control Equations and Reference Systemmentioning

confidence: 99%

“…Figure 2 shows the block diagram for the control of the DFIG from the rotor side using the rotor side converter (RSC). The current references i * rq and i * rd are calculated with (11) and (12) and with the required active and reactive power references. These current references are then compared with the real currents and the differences are the inputs signals of two PI regulators, obtaining in their outputs the references of the rotor voltage v * rq and v * rd .…”

Section: Dfig Control Equations and Reference Systemmentioning

confidence: 99%

“…DFIG generators provide access to the rotor windings and regulating the rotor voltage, the generator active and reactive powers are fully controllable. Therefore, the design and implementation of a new control scheme for a DFIG based wind turbine system has attracted the attention of several authors in the last years [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…In the work presented in [11] the authors propose a Power Delta Control for a wind turbine in order to participate in the primary and secondary frequency regulation. This work presents a readily industrializable set of algorithms for torque and pitch control.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Grid Frequency and Amplitude Control Using DFIG Wind Turbines in a Smart Grid

et al. 2021

View full text Add to dashboard Cite

Wind-generated energy is a fast-growing source of renewable energy use across the world. A dual-feed induction machine (DFIM) employed in wind generators provides active and reactive, dynamic and static energy support. In this document, the droop control system will be applied to adjust the amplitude and frequency of the grid following the guidelines established for the utility’s smart network supervisor. The wind generator will work with a maximum deloaded power curve, and depending on the reserved active power to compensate the frequency drift, the limit of the reactive power or the variation of the voltage amplitude will be explained. The aim of this paper is to show that the system presented theoretically works correctly on a real platform. The real-time experiments are presented on a test bench based on a 7.5 kW DFIG from Leroy Somer’s commercial machine that is typically used in industrial applications. A synchronous machine that emulates the wind profiles moves the shaft of the DFIG. The amplitude of the microgrid voltage at load variations is improved by regulating the reactive power of the DFIG and this is experimentally proven. The contribution of the active power with the characteristic of the droop control to the load variation is made by means of simulations. Previously, the simulations have been tested with the real system to ensure that the simulations performed faithfully reflect the real system. This is done using a platform based on a real-time interface with the DS1103 from dSPACE.

show abstract

“…Equations (11) and (12) show that the stator active power is controlled with the q component of the rotor current and the stator reactive power with the rotor current d component.…”

Section: Dfig Control Equations and Reference Systemmentioning

confidence: 99%

Section: Dfig Control Equations and Reference Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Grid Frequency and Amplitude Control Using DFIG Wind Turbines in a Smart Grid

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In order to test the ideas of Section 2.1, we have put together the model shown by Figure 2 for the production of synthetic data. It uses the DTU 10 MW reference wind turbine model [84,85] for OpenFAST version 2.3 [86] compiled for Simulink and a turbine controller written by one of the authors [87,88]. The turbine controller produces, as usual [89], generator torque and blade pitch angle references based on the generator speed.…”

Section: Synthetic Datamentioning

confidence: 99%

A Sensor Data Processing Algorithm for Wind Turbine Hydraulic Pitch System Diagnosis

et al. 2021

Self Cite

View full text Add to dashboard Cite

Modern wind turbines depend on their blade pitch systems for start-ups, shutdowns, and power control. Pitch system failures have, therefore, a considerable impact on their operation and integrity. Hydraulic pitch systems are very common, due to their flexibility, maintainability, and cost; hence, the relevance of diagnostic algorithms specifically targeted at them. We propose one such algorithm based on sensor data available to the vast majority of turbine controllers, which we process to fit a model of the hydraulic pitch system to obtain significant indicators of the presence of the critical failure modes. This algorithm differs from state-of-the-art, model-based algorithms in that it does not numerically time-integrate the model equations in parallel with the physical turbine, which is demanding in terms of in situ computation (or, alternatively, data transmission) and is highly susceptible to drift. Our algorithm requires only a modest amount of local sensor data processing, which can be asynchronous and intermittent, to produce negligible quantities of data to be transmitted for remote storage and analysis. In order to validate our algorithm, we use synthetic data generated with state-of-the-art aeroelastic and hydraulic simulation software. The results suggest that a diagnosis of the critical wind turbine hydraulic pitch system failure modes based on our algorithm is viable.

show abstract

Providing power reserve for secondary grid frequency regulation of offshore wind farms through yaw control

Oudich,

Gyselinck,

De Belie

et al. 2023

Wind Energy

View full text Add to dashboard Cite

The ability to significantly contribute to the frequency regulation and provide valuable ancillary services to the transmission system operator (TSO) is one of the present wind farm (WF) challenges, due to the limitations of wind speed forecasting and insufficient power reserve in certain operating conditions notably. In this work, the feasibility of WFs to participate in frequency restoration reserve (FRR) through yaw control is assessed. To this end, a distributed yaw optimization method is developed to evaluate the power gain achieved by yaw redirection based on wind turbine cooperation and compared with a greedy approach. The method relies on a static wake model whose parameters are estimated in a systematic way from simulation data generated with FAST.Farm. Through a case study based on a scaled version of the Belgian Mermaid offshore WF, it is demonstrated that the requirements of the TSO are fulfilled both in terms of response time and level of power reserve for most wind directions. The assessment is limited to wind speeds below the rated speed of the considered wind turbines.

show abstract

On Wind Turbine Power Delta Control

Cited by 10 publications

References 22 publications

Grid Frequency and Amplitude Control Using DFIG Wind Turbines in a Smart Grid

Grid Frequency and Amplitude Control Using DFIG Wind Turbines in a Smart Grid

A Sensor Data Processing Algorithm for Wind Turbine Hydraulic Pitch System Diagnosis

Providing power reserve for secondary grid frequency regulation of offshore wind farms through yaw control

Contact Info

Product

Resources

About