Algoritmo de otimização por enxame de partículas discreto aplicado na alocação ótima de banco de capacitores em sistemas de distribuição

• Autor(a) principal: Agnese, Luís Henrique Chouay Dall'
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
• Texto Completo: http://tede.unioeste.br/handle/tede/4935
• topic: Alocação de capacitores; Algoritmo PSO; Algoritmo PSO discreto; Redução nas perdas de potência; Capacitor allocation; PSO algorithm; Discrete PSO algorithm; Power loss reduction; ENGENHARIAS::ENGENHARIA ELETRICA

The operation planning of an electrical system is a complex task. One of its activities is to analyse the operational conditions of the power network with the objective of evaluating alternatives and the procedures in order to control the voltages and the use of the system. One of the strategies used to work with this problem is the capacitor bank, since these devices are sources of reactive power energy, and the insertion of this energy in specific locations on the system leads to an improvement in operating voltage and a reduction in the level of local load operation. In this context, this work can define an optimal allocation of capacitor banks for regular reactive power flow in distribution systems. The problem is based on a mathematical model that minimizes the cost of system operating and investment in devices, where a sensitivity index and bars with low voltage levels are used to define the locals that are selected as candidates for allocation. Use the particule swarm optimization algorithm, adapted for a discrete version, seeking to determine the best quantity and the ideal location for the positioning of the capacitor bank. The algorithm was applied to the 10-, 34-, 69- and 85-bars systems tested present in the specialized literature. As a result, there was a reduction in the active power loss with the addition of a capacitor bank and an algorithm demonstrated a good solution compared to other optimization techniques present in the literature.