Optimizing Adaptive Disturbance Rejection Control Models Using the Chimp Optimization Algorithm for Ships' Hybrid...

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Theory

Background:

• Hybrid renewable energy systems are increasingly used in warships, but renewable energy sources introduce uncertainty.
• Maintaining stable voltage is critical for sensitive loads in these systems, especially during power disturbances.

Purpose of the Study:

• To implement a novel control strategy for a dynamic voltage restorer (DVR) in a hybrid solar power system for warships.
• To enhance the stability and robustness of the hybrid system against voltage disturbances.

Main Methods:

• A new metaheuristic-based Active Disturbance Rejection Control (ADRC) strategy was developed for DVR control.
• The Chimp Optimization Algorithm (ChOA) was used to tune ADRC parameters in real-time (ChOA-ADRC).
• The proposed system was evaluated under two- and three-phase fault scenarios and compared to a PI controller.

Main Results:

• The ChOA-ADRC strategy effectively corrected fault-induced voltage drops and maintained sensitive load voltage.
• The proposed control strategy demonstrated superior dynamic response compared to conventional methods.
• The hybrid power generation system's reliability was significantly increased.

Conclusions:

• The novel ChOA-ADRC strategy offers an effective solution for voltage regulation in hybrid renewable energy systems for warships.
• This approach enhances system resilience and performance under fault conditions.
• The real-time tuning capability of ChOA-ADRC contributes to improved system stability and reliability.