Desarrollo de herramientas computacionales para la planificación operativa de corto plazo de sistemas eléctricos de potencia en base a técnicas heurísticas : Herramienta computacional para la planificación operativa de corto plazo de sistemas eléctricos de potencia en base a algoritmos genéticos.

Abstract

The present Curricular Integration Work (CIW) consists in the development of a computational tool for solving the problem of short-term operational planning of electrical power systems through the heuristic technique of genetic algorithms (GA), programmed in Python language. The developed tool solves the short-term operational planning problem that represents a mixed integer optimization problem. Therefore, the objective function to be minimized, is the daily operating cost of thermal power plants (fuel costs, startup, and shutdown). To solve the problem, a single - node system was considered, that is, without considering the losses of the transmission system. The proposed methodology for the development of the genetic algorithm is based on the generation of the initial population, mutation, crossing and selection. The tool is tested with IEEE 14 and IEEE 39 bus electrical systems. The obtained results: power dispatched by each plant throughout the study period and total cost of operating the system are contrasted with existing references, as well as with the heuristic techniques of particle swarm and gray wolf, developed in parallel as a component of the project.