Fault-tolerant optimal pitch control of wind turbines using dynamic weighted parallel firefly algorithm.

Area of Science:

• Renewable Energy Systems
• Control Engineering
• Electrical Power Generation

Background:

• Wind turbine (WT) systems are increasingly vital for electrical energy generation.
• Enhancing WT efficiency and reliability necessitates robust fault-tolerance.
• Pitch control is critical for managing WT performance under various operating conditions.

Purpose of the Study:

• To develop an optimal fault-tolerant pitch control (FTPC) strategy for wind turbines.
• To improve WT performance and reliability in the presence of sensor, actuator, and system faults.
• To introduce a novel control scheme integrating fractional calculus and advanced optimization.

Main Methods:

• Implementation of a fractional-calculus based extended memory (EM) pitch control strategy.
• Utilization of a fractional-order proportional-integral-derivative (FOPID) controller.
• Employing a dynamic weighted parallel firefly algorithm (DWPFA) for controller parameter tuning.
• Evaluation on a 4.8-MW WT benchmark model and comparison with conventional methods.

Main Results:

• The proposed FTPC strategy demonstrated enhanced fault-tolerant capabilities.
• The control scheme maintained consistent power generation at a given wind speed, even under fault conditions.
• Comparative analysis showed superiority over conventional PI and basic FOPID controllers.

Conclusions:

• The developed optimal fault-tolerant pitch control strategy significantly improves WT reliability and performance.
• The integration of fractional calculus and DWPFA offers a promising approach for advanced WT control.
• The proposed method ensures more stable power output, crucial for grid integration.