Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains
Biofuels have been criticized for affecting the food market as well as for the additional strain placed on the limited agricultural resources. Biofuel supply chains are complex systems with multiple decisions makers. The logical approach in dealing with such problems would have to be based on game t...
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oai:animorepository.dlsu.edu.ph:etd_masteral-136862023-10-25T06:09:17Z Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains Barilea, Ivan Dale Uy Biofuels have been criticized for affecting the food market as well as for the additional strain placed on the limited agricultural resources. Biofuel supply chains are complex systems with multiple decisions makers. The logical approach in dealing with such problems would have to be based on game theory. This paper presents the development of a bi-level optimization model that accounts for multi-feedstock bioenergy systems and incorporates a multi-period framework, which gives a more accurate interpretation of the real world energy systems. The upper level decision maker (i.e. the national government) aims to maximize the social utility of the use of biofuel by properly setting biofuel policies or interventions (i.e. import tariffs, subsidies, environmental limits), while the lower level decision maker (i.e. biofuel industry) wants to maximize their profit subject to the limits or conditions proposed by the upper level decision maker. Government interventions or policies are used in the model to assist in suppressing undesirable behavior of the system. This is a Stackelberg game (i.e. a non-cooperative game between unequal players). Numerical case studies based on the Philippine biofuel system are shown to illustrate the methodology. The case studies show that, for both uncontrolled and controlled scenarios, complex interactions exist among the outputs of competing industrial sectors. It was determined that the effect of one intervention policy might be detrimental to the effect of other intervention policies, and that the magnitude of the intervention policy must be chosen properly to account for such interactions. This implies that providing unnecessary interventions that are meant to support the local production sector can actually do more harm than good for the bioenergy system. Understanding this concept will allow decision makers to develop more cost-effective policies. As mentioned, bioenergy supply chains consist of complex systems and having to tackle multiple decisions makers further adds to its difficulty. This leads to results that are counterintuitive, and allows decision makers to obtain insights not readily available from direct investigation. The simulations show that rational policy [10] De La Salle University interventions can be systematically imposed to suppress undesirable dynamic behavior in complex energy systems. The biofuel industry can be separated into the farmers and the biofuel conversion sectors, which would provide a more realistic interpretation of the system; this concept can be the subject of future research. 2012-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_masteral/6848 Master's Theses English Animo Repository Feedstock Biomass energy Chemical Engineering |
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Feedstock Biomass energy Chemical Engineering Barilea, Ivan Dale Uy Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains |
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Biofuels have been criticized for affecting the food market as well as for the additional strain placed on the limited agricultural resources. Biofuel supply chains are complex systems with multiple decisions makers. The logical approach in dealing with such problems would have to be based on game theory. This paper presents the development of a bi-level optimization model that accounts for multi-feedstock bioenergy systems and incorporates a multi-period framework, which gives a more accurate interpretation of the real world energy systems. The upper level decision maker (i.e. the national government) aims to maximize the social utility of the use of biofuel by properly setting biofuel policies or interventions (i.e. import tariffs, subsidies, environmental limits), while the lower level decision maker (i.e. biofuel industry) wants to maximize their profit subject to the limits or conditions proposed by the upper level decision maker. Government interventions or policies are used in the model to assist in suppressing undesirable behavior of the system. This is a Stackelberg game (i.e. a non-cooperative game between unequal players). Numerical case studies based on the Philippine biofuel system are shown to illustrate the methodology. The case studies show that, for both uncontrolled and controlled scenarios, complex interactions exist among the outputs of competing industrial sectors. It was determined that the effect of one intervention policy might be detrimental to the effect of other intervention policies, and that the magnitude of the intervention policy must be chosen properly to account for such interactions. This implies that providing unnecessary interventions that are meant to support the local production sector can actually do more harm than good for the bioenergy system. Understanding this concept will allow decision makers to develop more cost-effective policies. As mentioned, bioenergy supply chains consist of complex systems and having to tackle multiple decisions makers further adds to its difficulty. This leads to results that are counterintuitive, and allows decision makers to obtain insights not readily available from direct investigation. The simulations show that rational policy [10] De La Salle University interventions can be systematically imposed to suppress undesirable dynamic behavior in complex energy systems. The biofuel industry can be separated into the farmers and the biofuel conversion sectors, which would provide a more realistic interpretation of the system; this concept can be the subject of future research. |
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Barilea, Ivan Dale Uy |
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Barilea, Ivan Dale Uy |
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Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains |
title_short |
Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains |
title_full |
Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains |
title_fullStr |
Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains |
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Developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains |
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developing a bi-level multi-period multi-feedstock optimization model for bioenergy supply chains |
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Animo Repository |
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2012 |
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https://animorepository.dlsu.edu.ph/etd_masteral/6848 |
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