Regulating Frequencies Enhances Renewable Energy Power Systems

It is a tough topic of research to investigate how to improve the efficiency of the power system by utilizing renewable energy sources. The load frequency control (LFC) issues have been addressed by researchers through the use of several methods, such as the automated gain control (AGC) regulator, excitation controllers, and control plans, all in response to parameter uncertainties. A blackout in a contemporary power grid might affect a larger region due to unanticipated changes in demand and the unpredictability of renewable energy. In this case, a more sophisticated approach to controlling or regulating is required. The increasing popularity of controllers that employ optimization algorithms can be attributed to their ease of use, quick convergence, and the fact that most optimization-based controllers do not require a physical system model. To guarantee an optimal solution for LFC problems and cost optimization, this method makes use of two natural solutions: the Atom Search Optimization (ASO) and the Firefly Algorithm (FA). In our initial contribution, we used frequency regularization to construct a power system model that is related to renewable energy sources. Using this method, we have attempted to lower the steady-state errors to raise the power system's overall steady-state accuracy and performance.