Planejamento estático da expansão de sistemas de transmissão de energia elétrica utilizando otimização por enxame de partículas

Abstract

This dissertation aims at the realization of the static transmission network expansion planning (STNEP) of electric power systems using the Particle Swarm Optimization (PSO) method. The proposed methodology uses a Constructive Heuristic Algorithm (CHA) in order to pre-select the most relevant candidates lines for expansion, so as to reduce the search space and thereby increasing efficiency of the bioinspired optimization process. Thus, the proposed methodology can be divided into two steps: (i) Obtaining the reduced set of routes through the CHA, in order to identify relevant routes for expansion and thus reduce the search space; (ii) Using the Particle Swarm Optimization and heuristic information provided by the first stage, in order to find the minimum expansion cost using a reduced number of particles. In both stages the transmission network is represented by a linearized load flow model, where the expansion decisions are incorporated into the optimization problem using the original equations of the model DC. The selection of expansion criterion is done through heuristic in order to avoid combinatorial explosion associated with expansion alternatives. The proposed methodology is applied to the Garver system and two real equivalent South and Southeastern Brazilian systems.