Synergetic-PI controller based on genetic algorithm for DPC-PWM strategy of a multi-rotor wind power system

Area of Science:

• Renewable Energy Systems
• Control Engineering
• Power Electronics

Background:

• Multi-rotor wind energy (MRWE) conversion systems require advanced control for optimal energy extraction.
• Asynchronous generators (AG) are commonly used in MRWE systems, necessitating effective control strategies.
• Existing direct power control (DPC) methods may face challenges with fluctuating wind speeds and modeling uncertainties.

Purpose of the Study:

• To develop and evaluate a novel nonlinear control technique for AG-based MRWE systems.
• To improve the robustness and stability of MRWE systems under dynamic operating conditions.
• To achieve optimal energy extraction using a combined synergetic control, proportional-integral controller, and genetic algorithm (SC-PI-GA) approach.

Main Methods:

• A direct power control (DPC) strategy is proposed, integrating synergetic control (SC), a proportional-integral (PI) controller, and a genetic algorithm (GA), termed DPC-SPI-GA.
• The DPC-SPI-GA technique controls an asynchronous generator (AG) in MRWE systems, utilizing pulse width modulation (PWM) for the AG inverter.
• Active and reactive power are estimated via current and voltage measurements, eliminating the need for inner loops unlike field-oriented control (FOC).

Main Results:

• The proposed DPC-SPI-GA technique demonstrates stable control characteristics under random wind speed changes.
• The new nonlinear control strategy exhibits significant robustness against modeling uncertainties.
• Comparative tests validate the superior performance of the DPC-SPI-GA strategy over traditional DPC techniques.

Conclusions:

• The DPC-SPI-GA technique offers a powerful and integrated solution for controlling AG-based MRWE systems.
• This approach enhances energy extraction efficiency and system stability in variable wind conditions.
• The developed technique provides a robust alternative for advanced MRWE system control.