Autor(es)

Caetano, Henrique O. ; Desuo, N. Luiz ; Fogliatto, Matheus S. S. ; Maciel, Carlos D.

• Tipo de documento: Artigo Científico
• Fonte: Electric Power Systems Research; v. 216, p. 6-pg., 2023-01-12.

Resumo

Power Distribution Systems are considered critical infrastructures, and their continuity to deliver and maintain electricity to the final customer is of extreme importance. The Optimal Switch Allocation address this topic by changing the network configuration to improve reliability, while minimizing power loss and cost. On previous researches economic constraints and dynamic failure models were considered, but neither the uncertainty in the environmental parameters nor stochastic models are applied. Additionally, the possibility to upgrade existing switches are often not considered. This work applies a Genetic Algorithm, coupled with Monte Carlo Simulation, as well as a Bayesian Inference Model, to address the probability of upgrading existing switches in a power distribution system. Economical constraints, fragility curves, variable load demand and weather scenarios are simulated. The Bayesian inference allows the model to be used as a support decision tool, when dealing with the possibility of upgrading switches in the network, especially in face of uncertainties in the distribution system. Results show that the upgrade of existing switches can achieve total cost reduction, but the uncertainties presented in the model can change the probability of upgrading an individual switch, thus sustaining the importance of the proposed approach. (AU)

• Processo FAPESP: 14/50851-0 - INCT 2014: Instituto Nacional de Ciência e Tecnologia para Sistemas Autônomos Cooperativos Aplicados em Segurança e Meio Ambiente
• Beneficiário: Marco Henrique Terra
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 21/12220-1 - Análise da resiliência de sistemas de distribuição utilizando redes probabilísticas
• Beneficiário: Henrique de Oliveira Caetano
• Modalidade de apoio: Bolsas no Brasil - Doutorado Direto
• Processo FAPESP: 19/06531-4 - Análise da resiliência de sistemas elétricos utilizando redes complexas
• Beneficiário: Henrique de Oliveira Caetano
• Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
• Processo FAPESP: 18/19150-6 - Resiliência de sistemas complexos com o uso de redes bayesianas dinâmicas: uma abordagem probabilística
• Beneficiário: Carlos Dias Maciel
• Modalidade de apoio: Bolsas no Exterior - Pesquisa