Genetic Algorithm Applications to Power Management

With the rapid growth in energy demand due to the increasing population, industrialization, and technological advancements, effective energy management plays a pivotal role in maintaining a balance between energy demand and supply. This increase in energy demand can potentially result in significant economic or environmental implications. In this regard, many Machine Learning (ML)-based algorithms have been applied to develop power grids in order to increase their efficiency and reliability. Additionally, decreasing the cost of the system and limiting its negative effects are other benefits of applying optimization algorithms. In this study, we discuss the importance of applying the Genetic Algorithm (GA) which is an ML-based optimization algorithm in energy management, and review its applications in this field.