Enhancing Frequency Deviation of a Microgrid in Connected Mode Using Particle Swarm Optimization

The demand for electric power has been increasing salient lately, causing carbon emissions from energy goes up by more than half when compared to the period when the industrial revolution began, that raising concerns about global warming. As a result, the researchers focused on the movement toward renewable energy, including solar energy, wind energy, and biomass energy, rather than conventional energy, which depends on fuel. Because the generation point of electric power is relatively far from the point of consumption, therefore electric power transmission lines are the means of delivering energy to the consumer, it has become important to study the electrical system and develop the most appropriate solutions to the problems that occur in it. One of the researchers' top priorities is keeping the system's frequency stable. Various smart solutions were utilized in the researchers' studies to adjust the frequency stability of power systems. An artificial intelligence-based technique was utilized for modeling the proper control of the frequency of the microgrid, like the operation of the human brain. In this study, a model of a microgrid with a solar-energy station connected to the main grid was designed. The control that will use the PSO algorithm to enhance PID was compared and analyzed, and the smart controllers were designed and tested using MATLAB.