Optimized cascaded regulation strategy for robust automatic generation control in renewable-integrated power networks

Area of Science:

• Electrical Engineering
• Control Systems Engineering
• Renewable Energy Systems

Background:

• Linked Power Networks (LPNs) face challenges in maintaining voltage and frequency stability due to nonlinear dynamics and load variations.
• High penetration of intermittent renewable energy sources complicates traditional Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) schemes.
• Modern multi-area hybrid grids require advanced control strategies for fast, robust, and coordinated regulation.

Purpose of the Study:

• To develop and evaluate a novel cascaded control architecture for LFC and AVR in a three-area hybrid LPN.
• To enhance the transient response, robustness, and steady-state accuracy of voltage and frequency regulation.
• To optimize controller parameters using the Differential Creative Search (DCS) algorithm.

Main Methods:

• A cascaded control framework integrating FOPI, TIDμ, and PIDA regulators was designed for LFC and AVR.
• Controller parameters were optimized using the Differential Creative Search (DCS) algorithm.
• Simulations were conducted in MATLAB/Simulink and results compared against Artificial Ecosystem-based Optimization (AEO), Dandelion Optimizer (DO), and Runge-Kutta Optimization (RUN) algorithms, as well as other advanced controllers.

Main Results:

• The DCS algorithm achieved a superior objective function value of 0.0507, outperforming AEO, DO, and RUN.
• The proposed FOPI-TIDμ-PIDA controller demonstrated significant improvements over FOPI-PI, TFOIDFF, and FOPI-PIDD2 controllers.
• The controller achieved reduced overshoot (<0.12 Hz), faster settling times (<9.4 s), and enhanced regulation under parameter variations (±25%).

Conclusions:

• The proposed FOPI-TIDμ-PIDA controller offers superior performance in terms of stability, robustness, and adaptability for hybrid LPNs.
• The DCS optimization algorithm effectively tunes controller parameters for optimal performance.
• The developed control strategy enhances the stability and resilience of sustainable hybrid linked power networks.