A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system

Area of Science:

• Electrical Engineering
• Control Systems
• Renewable Energy Integration

Background:

• Maintaining power balance in multi-area power systems with diverse generation sources is complex.
• Integrating renewable energy alongside conventional units presents stability challenges for automatic load frequency control (ALFC).

Purpose of the Study:

• To introduce a novel, efficient controller for ALFC in a three-area, multi-source, deregulated power system.
• To evaluate the performance of a proposed controller against existing methods under various operating conditions.

Main Methods:

• A parallel combination of Tilted Integral Derivative (TID) and Integral Derivative with filter (IDN) controller was designed.
• Controller parameters were optimized using the advanced Coatis Optimization Algorithm (COA).
• System performance was analyzed with energy storage units (Redox Flow Batteries) and under different deregulated market transactions, including generation constraints.

Main Results:

• The proposed TID+IDN controller demonstrated superior performance compared to standalone TID and IDN controllers.
• Optimized using COA, the controller achieved a low Integral Time Absolute Error (ITAE) of 0.1233 for transient responses.
• Significant improvements in settling time for frequency deviations were observed across all three areas.

Conclusions:

• The novel TID+IDN controller, optimized by COA, offers a robust and effective solution for load frequency control in complex hybrid power systems.
• The controller's effectiveness is validated under deregulated market scenarios, energy storage integration, and system parameter variations.
• This approach significantly enhances transient stability and system performance compared to existing control strategies.