Genetic Algorithm and Simulated Quenching in EE Transmission Expansion Planning

Authors

Martínez Campo, Sergio

Valdez Cervantes, Libis

Burgos Rodriguez, Arthur José

Rodríguez Arias, Harold

Abstract

In the present article, it shows the evaluation of two heuristic optimization methods, called genetic algorithms AG and simulated tempering AS (Simulated Annealing), applied in order to find the best solution with the lowest cost in planning the expansion of a transmission network. of electric energy, which, in addition to meeting the expected demand, considers a list of candidate alternatives with known cost and transport capacity. With the development of the AG and AS algorithms, it is possible to guarantee the best optimization solution, measuring the computational cost of the algorithms. It was verified that the Genetic Algorithm optimization method is able to find the best optimal solution at a lower computational cost, compared to the Simulated Quenching algorithm. All results obtained in this work for the expansion of the system in an optimal way are satisfactory as they also meet all restrictions.