Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process

Bioenergy parks are integrated energy systems developed based on material and energy synergies among bioenergy and auxiliary plants to increase efficiency and reduce carbon emissions. However, the resulting high interdependence between component units results to a vulnerable network upon capacity di...

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Main Authors: Benjamin, Michael Francis D., Tan, Raymond Girard R., Razon, Luis F.
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Published: Animo Repository 2015
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1660
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2659/type/native/viewcontent
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-26592021-07-14T01:15:53Z Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process Benjamin, Michael Francis D. Tan, Raymond Girard R. Razon, Luis F. Bioenergy parks are integrated energy systems developed based on material and energy synergies among bioenergy and auxiliary plants to increase efficiency and reduce carbon emissions. However, the resulting high interdependence between component units results to a vulnerable network upon capacity disruptions (i.e., plant inoperability). Inoperability of one or more plants within a bioenergy park results in a deviation from an initial network configuration because of failure propagation. The consequences of such disruptions depend upon which component units caused the failure. In this work, a probabilistic multi-disruption risk index is developed to measure the net output change of a bioenergy park based on exogenously-defined plant disruption scenarios, whose probabilities are estimated using the analytic hierarchy process (AHP). This network index is an important measure of the system's robustness to an array of probabilistic perturbation scenarios. Such risk-based information can be used for developing risk management measures to reduce network vulnerability through increasing system redundancy and diversity. A bioenergy park case study is presented to demonstrate the computation of the multi-disruption risk index. © 2015 . 2015-10-14T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/1660 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2659/type/native/viewcontent Faculty Research Work Animo Repository Energy parks—Risk assessment Multiple criteria decision making Chemical Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Energy parks—Risk assessment
Multiple criteria decision making
Chemical Engineering
spellingShingle Energy parks—Risk assessment
Multiple criteria decision making
Chemical Engineering
Benjamin, Michael Francis D.
Tan, Raymond Girard R.
Razon, Luis F.
Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process
description Bioenergy parks are integrated energy systems developed based on material and energy synergies among bioenergy and auxiliary plants to increase efficiency and reduce carbon emissions. However, the resulting high interdependence between component units results to a vulnerable network upon capacity disruptions (i.e., plant inoperability). Inoperability of one or more plants within a bioenergy park results in a deviation from an initial network configuration because of failure propagation. The consequences of such disruptions depend upon which component units caused the failure. In this work, a probabilistic multi-disruption risk index is developed to measure the net output change of a bioenergy park based on exogenously-defined plant disruption scenarios, whose probabilities are estimated using the analytic hierarchy process (AHP). This network index is an important measure of the system's robustness to an array of probabilistic perturbation scenarios. Such risk-based information can be used for developing risk management measures to reduce network vulnerability through increasing system redundancy and diversity. A bioenergy park case study is presented to demonstrate the computation of the multi-disruption risk index. © 2015 .
format text
author Benjamin, Michael Francis D.
Tan, Raymond Girard R.
Razon, Luis F.
author_facet Benjamin, Michael Francis D.
Tan, Raymond Girard R.
Razon, Luis F.
author_sort Benjamin, Michael Francis D.
title Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process
title_short Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process
title_full Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process
title_fullStr Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process
title_full_unstemmed Probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process
title_sort probabilistic multi-disruption risk analysis in bioenergy parks via physical input-output modeling and analytic hierarchy process
publisher Animo Repository
publishDate 2015
url https://animorepository.dlsu.edu.ph/faculty_research/1660
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2659/type/native/viewcontent
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