Optimization and Performance Analysis of a Smart Grid at Times of Fault Outbreaks Using Artificial Intelligence Techniques

The use of renewable energy sources (RESs) to supply electricity to remote and rural areas has grown in popularity. This improves the sustainability and dependability of the electrical system, especially in places where it is challenging to extend electricity. However, because RESs are inconsistent and intermittent, integrating hybrid RESs comes with a number of challenges. One of the best randomized methods for solving optimization problems is the employment of metaheuristic algorithms. These algorithms can find appropriate solutions for optimization problems that rely on random search within the problem-solving space, random operator application, and trial-and-error procedures. This paper aim to presents an improved artificial bee colony (ABC) that is fuzzy logic-based technique for power quality enhancement and optimization in a smart grid system motivated by the gap. The performance analysis and optimization technique are presented. The strategy for a microgrid, aiming to balance demand and meet load all while cutting down on gas emissions and power generation costs. MATLAB/Simulink is used for simulation. The satisfactory results are achieved under a proposed technique.