Abstract
Global population growth and the rising demand for energy are closely linked, driving the need for more advanced electrical systems. As a result, load frequency control (LFC) systems have become crucial in addressing this demand. To establish an optimal generation control scheme, it is essential to leverage soft computing (SC) techniques. SC embodies a rational and systematic approach, utilizing heuristic theories and algorithms to solve complex problems. Recently, these approaches have been widely applied across various engineering disciplines and applied sciences. Consequently, SC methods are increasingly prevalent in both research and industry. This paper provides a comprehensive overview of several SC techniques and their applications within LFC systems. It specifically examines the utilization of SC techniques such as fuzzy computing, evolutionary computing, swarm intelligence, and neural networks, as well as their hybrid combinations. The paper assesses the capabilities and limitations of these techniques in modeling, simulation, and optimization of LFC systems. It includes a succinct description of each algorithm, and the notable work accomplished in this field. Finally, the paper identifies open issues and outlines future research directions, emphasizing the potential advancements in SC applications for LFC systems.