Diseño de una red Smart Metering, basado en algoritmos genéticos, aplicado a la regeneración urbana de la ciudad de Loja

Abstract

This thesis deals with the application of a “Genetic Algorithm" (GA) in a Smart Metering (SM) system for the best location of the "Data Concentration Unit" (DCU) in the “Urban Regeneration of the City of Loja" (RUL), belonging to zone 7 and operated by “Empresa Eléctrica Regional del Sur SA" (EERSSA). The algorithm is used for solving an NP-Complete (NPC) problem (Problems that present computational or combinatorial complexity), which uses stochastic methods such as “Monte Carlo" (seeks to solve problems through random variables) or “Meta-Heuristics" (MH) (used to solve complex computational problems) and based on the resolution of “Set Covering Problem" (SCP) problems (seeks to minimize the number of elements needed to cover a larger work surface applying a set of constraints). The fitness function is optimized to achieve a faster convergence, granting enough randomness not to walk the algorithm to local maximum or minimum of the solution, ensuring that the convergence is fortuitous.