Genetic Algorithm and Its Applications in Power Systems

These days, artificial intelligence (AI) techniques play a vital role in power systems. Among these techniques, the Genetic Algorithm (GA) is a practical tool for addressing complicated issues. The global optimum solution can be found with the help of GA, which is a kind of natural selection. Electrical engineering is a field of engineering research in which systems are both enormous and extremely complicated. This chapter investigates the utilization of a GA in the field of power systems to solve problems such as generation expansion planning (GEP) and unit commitment (UC). GA-based solutions can handle problems with high processing costs and numerous constraints. To overcome optimization challenges such as nonlinearity, GA employs features such as crossover and mutation. This chapter presents the theory, literature review, and applications of genetic algorithms in power systems. The formulation of each feature is presented, and the problem constraints are discussed. In addition, a GA framework applied to the GEP problem and simulation results were analyzed, which illustrates the practicality of the GA in the power system.