Power systems integrated with renewable energy sources represent inherently complex and nonlinear structures, often subject to significant frequency deviations and power oscillations, particularly during periods of production shortfall under dynamic and high-load conditions. Furthermore, continuous fluctuations in load demand contribute to variations in grid frequency, transmission line power flow, and the output of generation units. To address these challenges, modern power grids employ Automatic Generation Control (AGC) systems. AGC functions to restore system frequency to its nominal value by utilizing a control metric known as the Area Control Error (ACE), while also ensuring that scheduled inter-area power transfers are maintained at their predefined levels. Achieving production balance in such situations is highly challenging. To address this issue, advanced control techniques and rapid energy storage systems (ESS ) are required. ESS units, such as Capacitive Energy Storage (CES ) systems, exhibit remarkable capabilities in balancing production demand and grid frequency demand. These systems effectively reduce power frequency oscillations caused by sudden and variable load disturbances, thereby regulating the frequency of the power system.

Accordingly, this study investigates the influence of Compressed Energy Storage (CES) units on the performance of AGC within a robust, interconnected power system. Given that fuzzy control methodologies are known to outperform traditional techniques under highly dynamic and uncertain operational environments, a novel multi-stage intelligent fuzzy Proportional-Integral-Derivative controller with an integrated filter (1+PI), referred to as FPIDF (1+PI), is proposed. This advanced control strategy aims to improve the overall effectiveness and stability of AGC operations. Simulation outcomes substantiate the enhanced performance of the proposed controller relative to conventional approaches.