Adaptive control design and implementation for collective pitch in wind energy conversion systems

Lasheen, Ahmed; Elnaggar, Mahmoud M.; Yassin, H. M.

doi:10.1016/j.isatra.2019.11.019

Cited by 16 publications

(11 citation statements)

References 24 publications

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“…The pitch angle influences the generator and power generated during high wind speeds. The key advantages of the new controller are the robustness against the complexities of the WT model, maintaining reliability and stability of the closed-loop system, and its applicability in real-life operations [61].…”

Section: Hydraulic Pitch Controller (Hpc)mentioning

confidence: 99%

A Review of Control Techniques for Wind Energy Conversion System

Manna

Singh

Akella

2023

Int. j. eng. technol. innov.

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Wind energy is the most efficient and advanced form of renewable energy (RE) in recent decades, and an effective controller is required to regulate the power generated by wind energy. This study provides an overview of state-of-the-art control strategies for wind energy conversion systems (WECS). Studies on the pitch angle controller, the maximum power point tracking (MPPT) controller, the machine side controller (MSC), and the grid side controller (GSC) are reviewed and discussed. Related works are analyzed, including evolution, software used, input and output parameters, specifications, merits, and limitations of different control techniques. The analysis shows that better performance can be obtained by the adaptive and soft-computing based pitch angle controller and MPPT controller, the field-oriented control for MSC, and the voltage-oriented control for GSC. This study provides an appropriate benchmark for further wind energy research.

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Section: Hydraulic Pitch Controller (Hpc)mentioning

confidence: 99%

A Review of Control Techniques for Wind Energy Conversion System

Manna

Singh

Akella

2023

Int. j. eng. technol. innov.

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“…Many PABLE regulators are proposed in the region between cut-out and rated wind speeds (Asgharniaa et al, 2018; Boukhezzar et al, 2007; Camblong, 2008; Chen et al, 2019; Gao and Gao, 2016; Hatami et al, 2016; Lasheen et al, 2020; Oh et al, 2015; Rahimi and Asadi, 2019; Yuan et al, 2020; Yuan and Tang, 2017). On the contrary, the more important challenges of WT are the mechanical stresses (Abolvafaei and Ganjefar, 2019) and uncertainties (Jiao et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…A PID with adaptive self-tuning regulator (STR) is constructed by Hatami et al (2016), and gain scheduled PID is designed by Yuan and Tang (2017) or proportional–integral (PI) scheme of controller can be shown by Rahimi and Asadi (2019). Moreover, the combination of adaptive and PI controller has been designed by Lasheen et al (2020).…”

Section: Introductionmentioning

confidence: 99%

Dynamic sliding mode control of pitch blade wind turbine using sliding mode observer

Karami-Mollaee

Shojaei

Barambones

et al. 2022

Transactions of the Institute of Measurement and Control

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In a wind turbine (WT), the maximum power can be achieved using a suitable and smooth signal, which should be applied to the pitch angle of the blades (PABLE). On the contrary, the uncertainties of the WT models cause the fatigue due to the mechanical stresses. To overcome these two problems, dynamic sliding mode control (D-SMC) is used because it is robust against uncertainties and can suppress the chattering by providing smooth signals. In D-SMC, an integrator is located before the actuator, as a low-pass filter, to suppress the high-frequency chattering. Then, the states number of the overall augmented system is one more than the states number of the actual system. To control such an augmented system, the added state variable needs to be estimated and hence, a novel sliding mode observer (SMO) is proposed. A trusty comparison is also presented using the conventional sliding mode control (C-SMC) with the proposed SMO. To implement D-SMC and C-SMC, a new state feedback is applied to the turbine at first. Therefore, a linear model with uncertainty is obtained, where its input is the PABLE. Lyapunov theory is used to proof the stability of the proposed SMO, D-SMC, and also the C-SMC. The presented comparison demonstrates the advantages of the D-SMC with respect to the C-SMC in removing the chattering and simplicity in concept and in implementation.

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“…These methods usually classified into two main categories; Individual pitch control methods (ICP) [2,3], where each pitch position control controller designed separately. The collective pitch control methods (CPC) [4,5], where the pitch positions of all blades controlled together using the same pitch angle reference. In the CPC framework, many strategies have been suggested including, the PID control [6], the gain-scheduling control method [7], the Linear Parameter-Varying control [8], and the Linear Quadratic Gaussian control method [9].…”

Section: Introductionmentioning

confidence: 99%

A New Intelligent Fault-Tolerant Control Scheme for Wind Energy Systems under Actuator Faults

Bakri¹,

Boumhidi²

2020

EJEE

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A reliable fault-tolerant control model for wind turbines (WTs) is a prominent task to meet the control objectives under the presence of the actuator faults. To this aim, the main focus of the present article is the design of a new fault-tolerant control scheme to deal with both additive and multiplicative faults. The design of the proposed method includes two extreme learning machine (ELM) blocks; an ELM-baseline controller to keep the desired wind turbine performances, and fault-tolerant ELM-block to eliminate any possible actuator faults effect. The design process of the ELM controller and the ELM fault estimator are formulated in a way that they only depend on WT input-output data, which allows a much faster and more precise fault tolerance. The effectiveness of the ELM faulttolerant method is tested and compared to a sliding mode observer-based accommodation method using a 5-MW WT benchmark model. Simulation results validate the great performances of the proposed method.

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Adaptive control design and implementation for collective pitch in wind energy conversion systems

Cited by 16 publications

References 24 publications

A Review of Control Techniques for Wind Energy Conversion System

A Review of Control Techniques for Wind Energy Conversion System

Dynamic sliding mode control of pitch blade wind turbine using sliding mode observer

A New Intelligent Fault-Tolerant Control Scheme for Wind Energy Systems under Actuator Faults

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