Cooperative Adaptive Command Filtered Backstepping Control for EVs to UPS-Microgrid via Virtual Synchronous Generator

Area of Science:

• Electrical Engineering
• Control Systems
• Renewable Energy Systems

Background:

• Uninterruptible Power Supply (UPS)-microgrid systems with multiple electric vehicles (EVs) face state of charge (SoC) consistency issues.
• These problems stem from differential expansion and controller saturation, impacting system reliability.

Purpose of the Study:

• To propose an adaptive command filter sliding-mode control strategy for multiple EVs in UPS-microgrid systems.
• To address SoC consistency problems and improve system operating stability.

Main Methods:

• Developed an SoC consistency algorithm and power allocation strategy for multiple EVs using directed graph theory.
• Modeled virtual synchronous generators (VSGs) by incorporating synchronous generator (SG) rotor motion equations into inverter control.
• Implemented a low-pass filter (LFP) in voltage control to simulate SG excitation attenuation.
• Designed a backstepping control strategy with a command filter and sliding mode controller.

Main Results:

• The proposed strategy effectively resolves SoC consistency problems in multi-EV UPS-microgrid systems.
• The control strategy demonstrates improved operating stability by mitigating system errors in angle, frequency, and power output.
• Simulations validated the stability of the UPS-microgrid system and the effectiveness of the proposed control approach.

Conclusions:

• The adaptive command filter sliding-mode control strategy offers a robust solution for SoC consistency in multi-agent EV-based UPS-microgrids.
• The integration of VSG principles and advanced control techniques enhances overall system performance and reliability.