Authors: Madhusudan Kumar, Abhinav Kumar Singh, Prof. Vishal Mehtre
Abstract: Optimal Power Flow (OPF) is a crucial problem in power systems that involves generating power at minimum cost while ensuring safe and feasible operation. This problem is normally solved by using mathematical approaches but they are not always effective due to the problem's complexity. In this context, researchers have started to apply smart, nature-inspired algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). These techniques help find better solutions, even for complex problems. In this paper, we analyse these algorithms in terms of speed, accuracy, computational effort and robustness. After analysing results of various research papers, we find what algorithm works best under various power system conditions.
DOI: https://doi.org/10.5281/zenodo.20198493
