Partially observable Markov decision processes for optimal operations of gas transmission networks
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.
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Partially observable Markov decision processes for optimal operations of gas transmission networks
Semantic Scholar · Engineering · 2020
Abstract
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.