Planejamento da expansão de sistemas de distribuição através de técnica bioinspirada

Abstract

This work proposes a methodology to solve distribution networks planning problems considering demand uncertainties. The methodology is based on the Artificial Immune System metaheuristics. In the solution process, the interval mathematics is implemented within the power flow and inside it, load uncertainties are modeled. The input interval variables are the active and reactive loads in the system buses. The expected result is presented in an interval and consists of minimizing the cable costs installation, construction or reinforcement of substations plus the costs associated with energy losses and operation considering a planning horizon. For this, restrictions such as radiality, connectivity, power balance and physical equipment capacities were used. To determine the best network topology, another methodology was adopted to compare the intervals. The main objective of this work is to evaluate the impact of considering the uncertainties of demand in the planning of distribution networks compared with traditional deterministic models. The proposed algorithm is tested in systems well-known in the literature.