Load Frequency Control Optimization Using Mgo-Based Pidf in Three-Area Systems With Energy Storage

Maintaining the stability and reliability of power systems is a key function of load frequency control (LFC). However, issues such as load variations, network challenges, and introducing renewable energy sources complicate this task. Consequently, devising an efficient controller for LFC becomes a complex optimization issue. In this paper, we propose a distinctive controller for LFC built on a proportional-integral-derivative (PID) controller and a derivative filter (PIDF). To find the optimum parameters of PIDF controllers, use Mountain Gazelle Optimizer (MGO), an algorithm that draws inspiration from the behavior of mountain gazelles. The performance of this controller is contrasted with that of another PIDF controller that leverages the Harmony Search (HS) algorithm. The controllers are evaluated using a three-area non-reheat thermal system, both with and without storage systems like superconducting magnetic energy storage (SMES) and battery energy storage (BES). The Integral Time Absolute Error (ITAE) serves as the objective function for the assessment of these controllers. The MGO-based PIDF controller with Energy Storage (ES) works better than the HS-based PIDF controller with and without ES, as well as the MGO-based PIDF controller without ES, when ITAE, frequency deviation, and tie-line power deviation are taken into account. Furthermore, the MGO-based PIDF controller exhibits superior robustness and noise immunity compared to the others. In conclusion, the controller proposed in this paper presents a potential solution for LFC in contemporary power systems. Special Issue of AEIC 2024 (Electrical and Computer and System Engineering Session)