A Multilayer System and Optimization Framework for Team Dispatch Towards Service Recovery

Autor(es)

Desuo, N. Luiz ; Fogliatto, Matheus S. S. ; Caetano, Henrique O. ; Pereira, J. Benvindo R. ; London J, J. Joao B. A. ; Maciel, Carlos D.

• Tipo de documento: Artigo Científico
• Fonte: IEEE TRANSACTIONS ON RELIABILITY; v. N/A, p. 14-pg., 2023-09-19.

Resumo

Diverse socioeconomic impacts from power outages in distribution networks are often caused by failures, and estimating their location frequently requires dispatching crews. However, in-field crews can reduce outage areas by network reconfiguration using manually controlled switches. In previous studies, a preset patrolling strategy disregarding the fact that several layers of information are interdependent led to suboptimal recovery of reliability indices, despite the fact that there was eventual service restoration. Thus, this article introduces a bi-level optimization method in which its upper level identifies the number and sequence of restoration stages through switching operations, and its lower level maps out the fastest crew routes from road networks. In addition, Monte Carlo simulations followed by Bayesian models were performed to identify limitations and put forward prepositioning suggestions for crews based on community detection. Their results show that the proposed method is well capable of coupling patrolling procedures with service recovery processes by merging diverse layers of information. Bayesian models were well capable of calculating tradeoffs for several manual recovery tactics, in addition to reflecting the impact of road network topics on power distribution reliability. Ultimately, the suggested method proved suitable to reduce reliability indices by merging several information layers, given that patrolling strategies were optimized and service was restored efficiently. (AU)

• Processo FAPESP: 19/07665-4 - Centro de Inteligência Artificial
• Beneficiário: Fabio Gagliardi Cozman
• Modalidade de apoio: Auxílio à Pesquisa - Programa eScience e Data Science - Centros de Pesquisa em Engenharia
• 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: 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: 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