Otimização da relação custo benefício de projetos de eficiência energética do tipo baixa renda

Abstract

The electricity utilities are required to invest part of its net operating income in the implementation of energy efficiency projects, according to the National Electric Energy Agency (ANEEL). The low-income type design is part of portfolio of possible projects and captures most of this application. Thus, it becomes very important to create a methodology to scale projects of this type and direct decision making of utilities in Brazil. Bioinspired optimization methods deal with combinatorial and nonlinear problems, if the mathematical equations for calculating the cost benefit rate of energy efficiency projects in low-income type. This paper proposes two recognized bioinspired optimization methods, the Ant Colony Optimization (ACO) and the Particle Swarm Optimization (PSO) to calculate and optimize the cost effectiveness of energy efficiency regulatory projects, the low-income type. Thus, propose a scientific methods of sizing of the energy efficiency projects, while optimizing these projects, obtaining the best operating result, from the point of view of energy efficiency with the best cost to society.