Please use this identifier to cite or link to this item:
|Title:||Power Grid Optimization Using PSO and Genetic Algorithms|
|Abstract:||Abstract In this paper, we present the methodology used in the development of the Optimal Power Flow (OPF) program in the grid using two metaheuristic methods : Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) developed in MATLAB for objective functions relating to the grid, and these functions are not limited to the energy production cost in power plants, there are many aspects, including losses in electricity transmission lines, as well as the environmental aspect that has become one of the biggest concerns because the gases emitted by power plants represent a significant danger to the environment. Two only functions among the three mentioned ones are going to be optimized using the GA and PSO methods, which are: the production cost and the gases emission functions. The simulation results applied on the 30 Bus grid are very satisfactory and respecting all the constraints imposed previously. Keywords: Optimal Power Flow, Genetic Algorithms, Particle Swarm Optimization, MATLAB.|
|Appears in Collections:||Faculté des Sciences et de la technologie (FST)|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.