P-graph approach to criticality analysis in integrated bioenergy systems
The use of integrated bioenergy systems (IBS) is a prospective solution to address the emergent global demand for clean energy. The sustainability of IBS compared to stand-alone biomass processing facilities is achieved through integration of process units or component plants via their bioenergy pro...
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Main Authors: | , , , |
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Format: | text |
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Animo Repository
2017
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Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2258 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3257/type/native/viewcontent |
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Institution: | De La Salle University |
Summary: | The use of integrated bioenergy systems (IBS) is a prospective solution to address the emergent global demand for clean energy. The sustainability of IBS compared to stand-alone biomass processing facilities is achieved through integration of process units or component plants via their bioenergy products, by-products, wastes, and common utilities. However, such increased component interdependency makes the resulting integrated energy system vulnerable to capacity disruptions. IBS in particular are vulnerable to climate change-induced events (e.g., drought) that reduce the availability of biomass feedstocks in bioenergy production. Cascading failure due to such supply-side disruptive event is an inherent risk in IBS and may pose a barrier to the commercial-scale adoption of such systems. A previous study developed a risk-based criticality index to quantify the effect of a component’s disruption within integrated energy systems. This index is used to rank the component’s relative risk in the network based on the ripple effects of its disruption. In this work, a novel P-graph approach is proposed as an alternative methodology for criticality analysis of component units or plants in an IBS. This risk-based metric can be used for developing risk management polices to protect critical facilities, thereby increasing the robustness of IBS against disruptions. Two case studies on determining the criticality index of process units in an integrated biorefinery and component plants in a bioenergy park are used to demonstrate the effectiveness of this method. © 2017, Springer-Verlag Berlin Heidelberg. |
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