A multi-objective algorithm to determine patrol sequences for out-of-service nodes in power distribution feeders

Author(s)

Fanucchi, Rodrigo Z. ^[1] ; Bessani, Michel ^[2] ; Camillo, Marcos H. M. ^[1] ; Desuo Neto, Luiz ^[3] ; da S. Soares, Anderson ^[4] ; de Lima, Telma W. ^[4] ; London Jr, Joao B. A. ; Dantas, Luciano B. ^[1] ; Maciel, Carlos D. ^[5]

Affiliation

^[1] Copel Distribuicao SA, Curitiba, Parana - Brazil

^[2] Univ Fed Minas Gerais, Dept Elect Engn, Belo Horizonte, MG - Brazil

^[3] Univ Sao Paulo, Sch Engn Sao Carlos, Sao Carlos - Brazil

^[4] Univ Fed Goias, Informat Inst, Goiania, Go - Brazil

^[5] London Jr, Jr., Joao B. A., Univ Sao Paulo, Sch Engn Sao Carlos, Sao Carlos - Brazil

• Document type: Journal article
• Source: Electric Power Systems Research; v. 196, JUL 2021.
• Web of Science Citations: 0

Abstract

During outages, Distribution Operation Centers establish a restoration plan to isolate the area that is probably faulty and reconnect all functioning components of a feeder. Despite all technological advances made in the last few decades, the final step to locate the faulty point is taken visually by repair field crews based on a patrol sequence. There is a lack of procedures to determine patrol sequences in literature, which is usually performed by the repair crew itself. Therefore, this paper offers an introduction to define patrol sequences in a multi-objective context. Furthermore, the Multi-Objective Discrete Particle Swarm Optimization has been proposed by using the 3-Opt algorithm and initialization heuristics based on an RNN algorithm - MODPSO+RNN+LS(3-Opt)-, which emulates the decisions made by the repair crew in the field. Lastly, the MODPSO+RNN+LS(3-Opt) was evaluated based on the IEEE 37-node and 123-node test feeders. The obtained results cast light upon how the initialization heuristics and local search method improve the final set of patrol sequence. In addition, it is also possible to find how the multi-objective context of the problem increases its complexity and how likely decisions that are typically made by the field repair crew could be improved by an optimization technique. (AU)

• 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