Optimal blade pitch control for enhancing the dynamic performance of wind power plants via metaheuristic optimisers

Soued, Salah; Ebrahim, Mohamed A.; Ramadan, Haïtham Saad Mohamed; Becherif, Mohamed

doi:10.1049/iet-epa.2017.0214

Cited by 59 publications

(29 citation statements)

References 29 publications

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“…The GWO, PSO, and GA are meta-heuristic algorithms which can be applied for tuning in optimization problems. The standard objective functions applied by researchers for tuning the gains of the PI controller are the integral absolute of error (IAE), the Integral multiplied time square of error (ITSE), the integral square of error (ISE) and the Integral Time multiplied absolute of error (ITAE) [25,26]. These are presented in (5)- (8).…”

Section: Standard Objective Functionsmentioning

confidence: 99%

Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer

Sule

Mokhtar

Jamian

et al. 2020

IJECE

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The need for tuning the PI controller is to improve its performance metrics such as rise time, settling time and overshoot. This paper proposed the Grey Wolf Optimizer (GWO) tuning method of a Proportional Integral (PI) controller for fixed speed Wind Turbine. The objective is to overcome the limitations in using the PSO and GA tuning methods for tuning the PI controller, such as quick convergence occurring too soon into a local optimum, and the controller step input response. The GWO, the Particle Swarm Optimization (PSO), and the Genetic Algorithm (GA) tuning methods were implemented in the Matlab 2016b to search the optimal gains of the Proportional and Integral controller through minimization of the objective function. A comparison was made between the results obtained from the GWO tuning method against PSO and GA tuning techniques. The GWO computed the smallest value of the objective function minimized. It exhibited faster convergence and better time response specification compared to other methods. These and more performance indicators show the superiority of the GWO tuning method.

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Section: Standard Objective Functionsmentioning

confidence: 99%

Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer

Sule

Mokhtar

Jamian

et al. 2020

IJECE

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“…For this purpose, four various performance indices are used such as Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE), and Integral Time Square Error (ITSE). In this study, the commonly used optimization techniques in engineering optimization applications are considered such as Zeigler Nicolas (ZN), Simplex Algorithm (SA), Genetic Algorithm (GA), and Artificial Bee Colony (ABC) .…”

Section: Stability Regions Classification and Verificationmentioning

confidence: 99%

Robust non‐fragile approach to resilient design of PID‐based blade pitch control for wind energy conversion system

Ebrahim

Ramadan

Soliman

2019

Asian Journal of Control

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The design of a blade pitch controller (BPC) for wind energy conversion system (WECS) applications is load-dependent and has to be adjusted for each operating condition. Thus, BPC robustness is important for coping with the endless variations in operating conditions. The boundaries of a robust stability region are determined in regards to the controller parameters plane using their relevant set of polynomial inequalities via Referential Integrity between Routh-Hurwitz criterion and Root-Locus (RI-RH/RL) approach. Constrained and unconstrained stability regions respectively are defined through a novel hybrid control technique based on the combination of both RI-RH/RL and Kharitonov (Kh) theorem. The hybrid RI-Kh method is used for globally analyzing all vertex plants to ensure the proposed controller robustness, nonfragility, and resilience by selecting its parameters at the center of the robust stability region. The optimal BPC-PID parameters estimated using different optimization techniques are always located within the specified stability region. Thus, the capability of the RI-Kh approach in determining the most robust, non-fragile and resilient controller is verified. Through simulation results, the effectiveness of the proposed approach and its applicability to WECS' global stabilization are validated.

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“…The objective of control systems is to ensure a continuous supply of energy to the grid, maximize energy production, and mitigate dynamic and static mechanical loads. The pitch angle of the blade, the torque of the generator, and the frequency on the grid are the main parameters that must be controlled [42].…”

Section: Control Systemmentioning

confidence: 99%

“…However, MPPT control is also used in this region to smooth out abrupt changes in wind speed, where the mechanical restrictions of the pitch system do not allow a rapid response. Finally, region IV is where the wind turbine must be stopped even with a mechanical brake [42,43].…”

Section: Control Systemmentioning

confidence: 99%

Pitch Angle Optimization by Intelligent Adjusting the Gains of a PI Controller for Small Wind Turbines in Areas with Drastic Wind Speed Changes

et al. 2019

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The population growth demands a greater generation of energy, an alternative is the use of small wind turbines, however, obtaining maximum wind power becomes the main challenge when there are drastic changes in wind speed. The angle of the blades rotates around its longitudinal axis to control the effect of the wind on the rotation of the turbine, a proportional-integral controller (PI) for this angle achieves stability and precision in a stable state but is not functional with severe alterations in wind speed, a different response time is necessary in both cases. This article proposes a novel pitch angle controller based on auto-tuning of PI gains, for which it uses a teaching–learning based optimization (TLBO) algorithm. The wind speed and the value of the magnitude of the change are used by the algorithm to determine the appropriate PI gains at different wind speeds, so it can adapt to any sudden change in wind speed. The effectiveness of the proposed method is verified by experimental results for a 14 KW permanent magnet synchronous generator (PMSG) wind turbine located at the Universidad Autónoma de Querétaro (UAQ), Mexico.

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Optimal blade pitch control for enhancing the dynamic performance of wind power plants via metaheuristic optimisers

Cited by 59 publications

References 29 publications

Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer

Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer

Robust non‐fragile approach to resilient design of PID‐based blade pitch control for wind energy conversion system

Pitch Angle Optimization by Intelligent Adjusting the Gains of a PI Controller for Small Wind Turbines in Areas with Drastic Wind Speed Changes

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