Abstract

The production of maximum wind energy requires controlling various parts of medium to large-scale wind turbines (WTs). This paper presents a robust pitch angle control system for the rated wind turbine power at a wide range of simulated wind speeds by means of a proportional–integral–derivative (PID) controller. In addition, ant colony optimization (ACO), particle swarm optimization (PSO), and classical Ziegler–Nichols (Z-N) algorithms have been used for tuning the PID controller parameters to obtain within rated stable output power of WTs from fluctuating wind speeds. The proposed system is simulated under fast wind speed variation, and its results are compared with those of the PID-ZN controller and PID-PSO to verify its effeteness. The proposed approach contains several benefits including simple implementation, as well as tolerance of turbine parameters and several nonparametric uncertainties. Robust control of the generator output power with wind-speed variations can also be considered a significant advantage of this strategy. Theoretical analyses, as well as simulation results, indicate that the proposed controller can perform better in a wide range of wind speed compared with the PID-ZN and PID-PSO controllers. The WT model and hybrid controllers (PID-ACO and PID-PSO) have been developed in MATLAB/Simulink with validated controller models. The hybrid PID-ACO controller was found to be the most suitable in comparison to the PID-PSO and conventional PID. The root mean square (RMS) error calculated between the desired power and the WT’s output power with PID-ACO is found to be 0.00036, which is the smallest result among the studied controllers.

Highlights

  • Environmental issues are one reason for the increasing popularity of renewable energy

  • We have proposed three hybrid pitch angle controllers for automatic power adjusting within the rated power of a 500 kW WTG system at the operating regions of wind turbines (WTs) under variable wind speeds

  • A PID-ant colony optimization (ACO)-based robust pitch angle controller is designed for a wind turbine to obtain stable rated WT output power from the fluctuating wind speed

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Summary

Introduction

Environmental issues are one reason for the increasing popularity of renewable energy. The hybrid algorithm particle swarm optimization (PSO)–radial basis function neural network (RBFNN) was proposed by Perng et al to achieve optimal PID parameters for WT control design [14] Another investigation was found based on fuzzy–proportional–derivative for large WTs operating above rated power to investigate a blade pitch control [15]. Iqbal, A. et al [17] have proposed an FLC pitch angle controller in a 1.5 MW wind turbine to maximum wind power production and minimum rotor speed along with torque They found optimum torque with pitch angle control by some blade parameters. This study initiated the design of a PID-ACO and PID-PSO based robust pitch angle controller to achieve rated wind power across a wide range of wind speeds.

Wind Turbine Model
Profile of Wind Speed
Actuator Model
Controller Design
Ant Colony Algorithm
Particle Swarm Optimization
Simulation Evaluation
ACO Method
Result
Findings
Conclusions
Full Text
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