Algoritmos bioinspirados aplicados ao problema de alocação de geração distribuída

• Autor(a) principal: Santos, Josephy Dias
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/12831
• topic: Algoritmo genético de Chu-Beasley; Symbiotic organisms search; Algorítimo de otimização do coronavírus; Geração distribuída; Sistemas elétricos de potência; Chu-Beasley genetic algorithm; Symbiotic organisms search; Coronavirus optimization algorithm; Distributed generation; Electrical power systems; OUTROS

This work presents the performance comparison of different meta-heuristics, two classic and one modern. The implemented optimization algorithms aim to solve the distributed generation allocation problem in electricity distribution networks widely known in the literature. The study confronts the following computational techniques applied in algorithms classified as bioinspired: the Chu-Beasley Genetic Algorithm (AGCB), the Symbiotic Organisms Search (SOS) and the Coronavirus Optimization Algorithm (CVOA). The allocation of DG units in the Electric Power System gives the system advantages and disadvantages. Among the advantages we can mention: reduction of power losses, expansion of investments in the electrical sector, expansion and diversification of the electrical matrix, mostly, use of clean energy and indirect benefits such as job creation. Among the disadvantages are difficulties in charging for the use of the electrical system, possible incidence of undue taxes, need to change operating procedures, indiscriminate elevation of the voltage profile if the penetration factor is high and the allocation of DG is random, increase in short circuit levels, failures in the protection operation, among others. The network operating conditions are verified through the forward and reverse sweep method, specifically using the Power Sum Method. The objective function, in the optimization model for the allocation of distributed generation, aims to minimize the total losses of active power in the system. For the implementations, the allocation of modules (100, 200 and 500kW) of distributed generation is considered, with the number of these modules limited by the penetration factor of each network. The specialized algorithms are tested on four electrical systems: 10, 34, 70 and 126 buses. The results obtained show the rapid convergence and robustness of the AGCB of the implemented algorithms, the same cannot be said about SOS, which had an intermediate performance. The CVOA, as an unprecedented contribution in this work, presented a lower performance than expected, largely due to its nature and architecture of the proposed modeling.