Nonlinear analysis of gain scheduled controllers for the NREL 5-MW turbine blade pitch control system

Poureh, Ali; Chamani, Mohammad; Bahri, Abbas

doi:10.1016/j.ijepes.2022.108578

Cited by 9 publications

(3 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Comprising the wind rotor, gearbox, and generator, the wind turbine's pitch system is equipped with a standard pitch controller (baseline PI) and a torque controller 26 . Refer to The baseline PI controller, as a proportional-integral controller, has been thoroughly examined and adopted as the benchmark controller [26][27][28] . In order to ensure fairness and evaluate the controller's uniformity in the simulation environment, we choose the baseline PI as the benchmark for the controller.…”

Section: Simulation Modelingmentioning

confidence: 99%

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Zhou,

Wang,

Jiang

et al. 2024

Preprint

View full text Add to dashboard Cite

In the context of wind energy systems, maintaining optimal power output in wind turbines when wind speeds exceed rated values necessitates precise regulation of blade pitch through the pitch control system. However, challenges in accurately modeling nonlinear control systems and enhancing control responsiveness arise due to factors such as actuator constraints, unmodeled dynamics, and random wind speed fluctuations. This paper proposes an improved model-free control, termed Input-Output Model-Free Adaptive Control (IO-MFAC). It enhances the system's adaptability to stochastic wind and improves tracking capabilities by adaptively adjusting the input difference based on the output difference through the new cost function. Moreover, to demonstrate the stability of IO-MFAC, its monotonic convergence is theoretically confirmed. Simulations conducted on the FAST simulator and hardware-in-the-loop experiments demonstrate that IO-MFAC outperforms basic MFAC under constant wind and turbulent conditions, exhibiting superior dynamic tracking performance, control effectiveness, and practical utility.

show abstract

Section: Simulation Modelingmentioning

confidence: 99%

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Zhou,

Wang,

Jiang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In order to optimize performance and extend the lifetime of the wind power generator, the key to its maintenance is optimal pitch control. This enables real-time analysis of hazardous situations based on data generated from various sensors and components of wind turbines [6,7]. Accordingly, the pitch control was performed by analyzing the wind speed/direction/temperature in real time using fuzzy rules, FIS, and WEKA data mining cluster analysis, and the effect was verified through computer simulation [8][9][10][11].…”

Section: Optimal Pitch Control Technology For Wind Power Generatorsmentioning

confidence: 99%

Wind Turbine Fire Prevention System Using Fuzzy Rules and WEKA Data Mining Cluster Analysis

Kim¹,

Park²,

Park³

et al. 2023

Energies

View full text Add to dashboard Cite

With the rapid expansion of the supply of renewable energy in accordance with the global energy transition policy, the wind power generation industry is attracting attention. Subsequently, various wind turbine control technologies have been widely developed and applied. However, there is a lack of research on optimal pitch control, which detects wind direction and changes the rotation angle of the blade in real time. In areas where the wind speed is not strong, such as South Korea, it is necessary to maintain the optimal angle in real time so that the rotating surface of the blade can face the wind direction. In this study, optimal pitch control was performed through real-time analysis of wind speed, direction, and temperature, which is the core of wind turbine maintenance, using fuzzy rules using FIS (Fuzzy Interface System) and WEKA data mining cluster analysis techniques. In order to prevent fires caused by the over-current of wind turbines, over-current control methods such as VCB (Vacuum Circuit Breaker) utilization, prototype utilization such as a modular MCB (Main Circuit Breaker) incorporating VI (Vacuum Interrupter), and vacuum degree change analysis methods using a PD (Partial Discharge) signal were proposed. The optimal control technique for wind turbine parts and facilities was put forth after judging and predicting the annual average wind distribution suitable for wind power generation using HRWPRM (Korea’s High-Resolution Wind Power Resource Maps). Finally, the various wind turbine control methods carried out in this study were confirmed through computer simulation, such as remote diagnosis and early warning issuance, prediction of power generation increase and decrease situation, and automatic analysis of wind turbine efficiency.

show abstract

“…Among the various methods available, variable gain controllers have been widely used for variable speed wind turbines [15,16] while using Linear Parameter Varying (LPV) models [17]. However, these methods did not maximize performance while limiting mechanical fatigue of the system.…”

mentioning

confidence: 99%

Investigation of the Robust Fractional Order Control Approach Associated with the Online Analytic Unity Magnitude Shaper: The Case of Wind Energy Systems

Mseddi,

Abid,

Naifar

et al. 2024

Fractal Fract

View full text Add to dashboard Cite

This paper investigates the development of a novel analytic approach for computing Unity Magnitude (UM) shapers that deviates from established numerical methodologies. The experimental validation on a test bench confirms the practicality and benefits of the suggested UM shaper technique. The study extends the use of UM shapers to improve the control of wind conversion systems (WCSs), particularly those including hybrid excitation synchronous generators (HESGs), demonstrating their adaptability and versatility. Experimental validation guarantees real-world application, confirming the suggested UM shapers’ trustworthiness. Strict management is still required to assure the system’s efficiency and dependability. In reality, the dynamic equations of a turbine, as well as those of an HESG, are substantially nonlinear; most system parameters are very uncertain; and, finally, a WCS is always impacted by disturbance sources such as load variations, harmonics, and mechanical vibrations. Robust control measures must be used to overcome these issues. A CRONE controller (Robust Fractional Order Control) of the second generation is created. A comparative study performed on the Simulink platform reveals substantial gains brought about by UM shapers in real-world circumstances. The study demonstrates the effectiveness of UM-shaped inputs in mechanical stabilization and Maximum Power Point Tracking (MPPT), emphasizing both theoretical soundness and practical advantages. The analytic equations for UM shapers in undamped and damped systems, offered together with a real-time algorithm, contribute to the optimization of wind conversion systems.

show abstract

Nonlinear analysis of gain scheduled controllers for the NREL 5-MW turbine blade pitch control system

Cited by 9 publications

References 32 publications

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Enhancing the Tracking Performance of Wind Turbine Blade Pitch Angle Control via Model-Free Adaptive Control Algorithm Utilizing Input-Output Differential

Wind Turbine Fire Prevention System Using Fuzzy Rules and WEKA Data Mining Cluster Analysis

Investigation of the Robust Fractional Order Control Approach Associated with the Online Analytic Unity Magnitude Shaper: The Case of Wind Energy Systems

Contact Info

Product

Resources

About