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

Author(s)

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

• Document type: Journal article
• Source: IEEE TRANSACTIONS ON RELIABILITY; v. N/A, p. 14-pg., 2023-09-19.

Abstract

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)

• FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
• Grantee: Fabio Gagliardi Cozman
• Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
• FAPESP's process: 21/12220-1 - Resilience analysis of distribution systems using probabilistic networks
• Grantee: Henrique de Oliveira Caetano
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• FAPESP's process: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment
• Grantee: Marco Henrique Terra
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 18/19150-6 - Resilience of complex systems with the use of dynamic Bayesian networks: a probabilistic approach
• Grantee: Carlos Dias Maciel
• Support Opportunities: Scholarships abroad - Research