P-graph approach to optimal allocation of electricity to economic sectors in crisis conditions
Rational allocation of scarce resources in a crisis is an integral part of risk management. In the case of energy systems, for example, the onset of climate change is expected to increase the frequency of extreme weather events which will further affect not only the reliability of electricity transm...
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Main Authors: | , , , , , , |
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Format: | text |
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Animo Repository
2014
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Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1585 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2584/type/native/viewcontent |
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Institution: | De La Salle University |
Summary: | Rational allocation of scarce resources in a crisis is an integral part of risk management. In the case of energy systems, for example, the onset of climate change is expected to increase the frequency of extreme weather events which will further affect not only the reliability of electricity transmission and fuel resource delivery but also test the integrity of energy infrastructure systems. Electricity supply is essential to all economic sectors and the onset of an energy crisis resulting from a calamity, an accident, an infrastructure failure or a political dispute will affect the productivity of the entire economy. Furthermore, the interdependencies between sectors can cause "ripple effects" to occur. Input-output models are an established methodology for quantifying such linkages in an economic system. During a power crisis, it is essential to provide a rational basis for allocation of limited energy supply in order to minimize its economic ripple effects. The best allocation for damage control can be determined by representing an input-output system as a P-graph model. The latter is a graph-T heoretic approach originally developed for chemical process design applications, and the analogous problem structures allow it to be used for the optimal allocation of electricity to various economic sectors in the event of a power crisis. We demonstrate the methodology using a case study based on Philippine input-output data. © 2014 The Authors. |
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