Optimization of automatic generation controllers in renewable multi-area power systems using the Fata Morgana...

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Theory

Background:

• Renewable energy integration causes intermittency and fluctuations in multi-area power systems (MAPS).
• Automatic Generation Control (AGC) is crucial for maintaining power system stability.
• Existing control methods struggle with the dynamic challenges posed by hybrid power systems.

Purpose of the Study:

• To develop and optimize an AGC framework for a two-area hybrid power system (solar, wind, thermal).
• To evaluate the performance of different controllers (PI, PIDn, FOPI, PPIDn) optimized by metaheuristic algorithms.
• To introduce and validate the novel Fata Morgana Algorithm (FATA) for AGC parameter tuning.

Main Methods:

• Implementation of an AGC framework for a hybrid two-area power system.
• Optimization of four controller types using four metaheuristic algorithms (GJO, ECO, ESC, FATA).
• Performance evaluation based on Integral Time Absolute Error (ITAE) and real-time validation on OPAL-RT OP5707.

Main Results:

• The FATA-optimized PIDn controller achieved the best dynamic performance with an ITAE of 0.18676.
• FATA demonstrated a performance improvement of over 4.6% compared to the ESC algorithm.
• Real-time validation confirmed the effectiveness of the FATA-based control strategy in enhancing frequency stability.

Conclusions:

• The Fata Morgana Algorithm (FATA) is a novel and efficient method for optimizing AGC parameters.
• The proposed FATA-based PIDn controller significantly enhances frequency stability in renewable-based MAPS.
• The study validates the practical feasibility of FATA for real-world power system control applications.