The design of energy systems usually requires technical, economical and environmental analysis. However, the growth of systems failure due to unpredictable low-probability external events makes the consideration of resilience in this design also important. Although there is no standard metric for resilience quantification yet, it is known that it should consider system configuration, operation time and total or partial energy generation during and after the event, as well as the components repair probability and time. A proposal for resilience quantification in four cogeneration plants was previously developed based on components stochastic failures and verification of their consequences in the plant energy generation. The present work aims to continue the development of this metric by including in its calculation the repair probability of the components, their repairing time and the plant downtime during the repair, essential parameters for resilience quantification. Two new metrics are proposed and simulations with 0, 50% and 75% of repair probability of the components are made in software CLIPS. One of the metrics is able to evaluate the influence of repairment in system resilience, while the other one predicts plant downtime during operation. The metrics point to S#2 as the most resilient system and S#3 as the most affect by repairing.
How to Cite
Resilience, Energy System, Cogeneration
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.