Partially observable Markov decision processes for optimal operations of gas transmission networks

Michele Compare, Piero Baraldi, Paolo Marelli and Enrico Zio

Reliability Engineering and System Safety, 2020, vol. 199, issue C

Abstract: We develop a decision-support framework based on Partially Observable Markov Decision Processes (POMDPs) for the management of Gas Transmission Networks (GTNs) operations, encoding realistic degradation state estimations provided by Prognostics and Health Management (PHM) systems, while considering demand variations and the effects of the management decisions on the GTN degradation evolution. This Operation and Maintenance (O&M) framework allows optimally operating a GTN. Furthermore, the economic impact of using PHM systems with different accuracy levels can be estimated. The approach is shown with reference to a GTN of the literature.

Keywords: Partially observable Markov decision Processes; Prognostics and health management; Degradation state estimation errors; Gas transmission network (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:199:y:2020:i:c:s0951832019302753

DOI: 10.1016/j.ress.2020.106893

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