A risk-based criticality analysis in bioenergy parks using P-graph method

The adoption of bioenergy parks is a prospective solution to increase the sustainability of stand-alone biomass processing plants. Production and resource efficiency, lower carbon emissions, and economic sustainability are achieved by synergistic exchanges of material and energy resources between co...

Full description

Saved in:
Bibliographic Details
Main Authors: Benjamin, Michael Francis D., Cayamanda, Christina D., Belmonte, Beatriz A., Tan, Raymond Girard R., Razon, Luis F.
Format: text
Published: Animo Repository 2016
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/280
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1279&context=faculty_research
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
id oai:animorepository.dlsu.edu.ph:faculty_research-1279
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:faculty_research-12792021-05-05T06:21:57Z A risk-based criticality analysis in bioenergy parks using P-graph method Benjamin, Michael Francis D. Cayamanda, Christina D. Belmonte, Beatriz A. Tan, Raymond Girard R. Razon, Luis F. The adoption of bioenergy parks is a prospective solution to increase the sustainability of stand-alone biomass processing plants. Production and resource efficiency, lower carbon emissions, and economic sustainability are achieved by synergistic exchanges of material and energy resources between components plants. However, such increased plant interdependency and the resulting integrated energy system is vulnerable to capacity disruptions. Cascading failure due to such disruptive event is an inherent risk in bioenergy parks and may pose as a barrier in implementing such system. The extent of risk originating from disrupted critical component plants in the network exhibited to be higher. A previous study developed a novel risk-based criticality index, based on input-output models, to quantify the effect of a component plant's disruption within a bioenergy park. This index is used to rank the plant's relative risk in the network based on its disruption consequence. In this work, a P-graph approach is proposed as an alternative methodology for criticality analysis of component plants in a bioenergy park. The P-graph framework is initially developed for solving process network synthesis, but recently being used to solve similarly structured problems. This risk-based metric can also be used for developing risk management measures to protect critical infrastructures, thereby increasing the robustness of bioenergy parks against disruptions. A case study is then presented to demonstrate the effectiveness of this method. Copyright © 2016, AIDIC Servizi S.r.l. 2016-01-01T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/faculty_research/280 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1279&context=faculty_research Faculty Research Work Animo Repository Energy parks Chemical Engineering Energy Systems
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
Chemical Engineering
Energy Systems
spellingShingle Energy parks
Chemical Engineering
Energy Systems
Benjamin, Michael Francis D.
Cayamanda, Christina D.
Belmonte, Beatriz A.
Tan, Raymond Girard R.
Razon, Luis F.
A risk-based criticality analysis in bioenergy parks using P-graph method
description The adoption of bioenergy parks is a prospective solution to increase the sustainability of stand-alone biomass processing plants. Production and resource efficiency, lower carbon emissions, and economic sustainability are achieved by synergistic exchanges of material and energy resources between components plants. However, such increased plant interdependency and the resulting integrated energy system is vulnerable to capacity disruptions. Cascading failure due to such disruptive event is an inherent risk in bioenergy parks and may pose as a barrier in implementing such system. The extent of risk originating from disrupted critical component plants in the network exhibited to be higher. A previous study developed a novel risk-based criticality index, based on input-output models, to quantify the effect of a component plant's disruption within a bioenergy park. This index is used to rank the plant's relative risk in the network based on its disruption consequence. In this work, a P-graph approach is proposed as an alternative methodology for criticality analysis of component plants in a bioenergy park. The P-graph framework is initially developed for solving process network synthesis, but recently being used to solve similarly structured problems. This risk-based metric can also be used for developing risk management measures to protect critical infrastructures, thereby increasing the robustness of bioenergy parks against disruptions. A case study is then presented to demonstrate the effectiveness of this method. Copyright © 2016, AIDIC Servizi S.r.l.
format text
author Benjamin, Michael Francis D.
Cayamanda, Christina D.
Belmonte, Beatriz A.
Tan, Raymond Girard R.
Razon, Luis F.
author_facet Benjamin, Michael Francis D.
Cayamanda, Christina D.
Belmonte, Beatriz A.
Tan, Raymond Girard R.
Razon, Luis F.
author_sort Benjamin, Michael Francis D.
title A risk-based criticality analysis in bioenergy parks using P-graph method
title_short A risk-based criticality analysis in bioenergy parks using P-graph method
title_full A risk-based criticality analysis in bioenergy parks using P-graph method
title_fullStr A risk-based criticality analysis in bioenergy parks using P-graph method
title_full_unstemmed A risk-based criticality analysis in bioenergy parks using P-graph method
title_sort risk-based criticality analysis in bioenergy parks using p-graph method
publisher Animo Repository
publishDate 2016
url https://animorepository.dlsu.edu.ph/faculty_research/280
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1279&context=faculty_research
_version_ 1699251187365183488