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 al algoritmo del lobo gris.

Abstract

Hydrothermal economic dispatch problem reaches out the ideal generation scheme that allows the production costs associated with the use of fuel and water to be minimized. The following Curricular Integration Work presents the development of a software tool in Python programming language to carry out the economic dispatch through the heuristic technique of the Gray Wolf Optimizer that seeks to minimize the cost of hydrothermal generation and thus provide a solution to the problem of short-term operational planning in electric power systems. The objective function is represented by the operating costs of the thermal power plants and the operating constraints of the system such as production limits, start-up and shutdown constraints, and operating time. In addition to considering reservoir storage limits, flow rates and safety volumes for hydroelectric systems. The complexity of the problem was reduced with lossless modeling of the transmission system (uninodal model) and linear approximation of the objective function. The tool was tested on the IEEE 14 and 39-bus test systems where the results were obtained are the generation powers of each plant for the whole planning period (24 hours) and the operating costs of the system. These values were validated with previously presented works and contrasted with two optimization algorithms which are Genetic Algorithms (GA) and Particle Swarm Optimizer (PSO).