Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties

Generally, synthesis and design of an optimal process is a challenging task. The procedure includes specifying and optimizing system configurations in order to achieve a certain aspect, such as maximizing economic performance, minimizing environmental impact, etc. However, uncertainties of the desig...

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Main Authors: Kasivisvanathan, Harresh, Ubando, Aristotle T., Ng, Denny K.S., Tan, Raymond Girard R.
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Published: Animo Repository 2014
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/3643
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4645/type/native/viewcontent/ie401824j.html
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-46452022-06-21T05:34:12Z Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties Kasivisvanathan, Harresh Ubando, Aristotle T. Ng, Denny K.S. Tan, Raymond Girard R. Generally, synthesis and design of an optimal process is a challenging task. The procedure includes specifying and optimizing system configurations in order to achieve a certain aspect, such as maximizing economic performance, minimizing environmental impact, etc. However, uncertainties of the design parameters (e.g., volatility of raw materials and products price, variability of feedstock supply and product demand, etc.) may undermine the effectiveness of such systematic design approaches. In response to this issue, various optimization works have been presented to address such problems. In this paper, a robust mixed integer linear programming (MILP) with input-output model is presented to aid decision-makers in addressing process synthesis problems due to uncertainties that arise from variation in feedstock supply and product demand. This work primarily encompasses multifunctional energy systems that can be described by a system of linear equations, which entails "black box" modeling. The robust model helps to determine the design capacity of each process unit in a flexible network which involves sizing of equipment. This network is assumed to be able to operate in all uncertain scenarios considered, with a minimum cost of the plant. In addition, the intended model also helps to determine the requirement to operate additional equipment in a plant in the presence of uncertainties. This is especially true with designs of plants that are incapable of meeting any increase in demand. These aspects of the work are novel and an important contribution as such analysis is not available in the literature, to date. Three case studies that include a polygeneration plant and palm oil based integrated biorefinery are presented to demonstrate the proposed novel approach in a more descriptive manner. © 2014 American Chemical Society. 2014-02-26T08:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/3643 info:doi/10.1021/ie401824j https://animorepository.dlsu.edu.ph/context/faculty_research/article/4645/type/native/viewcontent/ie401824j.html Faculty Research Work Animo Repository Polygeneration systems Robust optimization Biomass energy--Refining 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 Polygeneration systems
Robust optimization
Biomass energy--Refining
Energy Systems
spellingShingle Polygeneration systems
Robust optimization
Biomass energy--Refining
Energy Systems
Kasivisvanathan, Harresh
Ubando, Aristotle T.
Ng, Denny K.S.
Tan, Raymond Girard R.
Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties
description Generally, synthesis and design of an optimal process is a challenging task. The procedure includes specifying and optimizing system configurations in order to achieve a certain aspect, such as maximizing economic performance, minimizing environmental impact, etc. However, uncertainties of the design parameters (e.g., volatility of raw materials and products price, variability of feedstock supply and product demand, etc.) may undermine the effectiveness of such systematic design approaches. In response to this issue, various optimization works have been presented to address such problems. In this paper, a robust mixed integer linear programming (MILP) with input-output model is presented to aid decision-makers in addressing process synthesis problems due to uncertainties that arise from variation in feedstock supply and product demand. This work primarily encompasses multifunctional energy systems that can be described by a system of linear equations, which entails "black box" modeling. The robust model helps to determine the design capacity of each process unit in a flexible network which involves sizing of equipment. This network is assumed to be able to operate in all uncertain scenarios considered, with a minimum cost of the plant. In addition, the intended model also helps to determine the requirement to operate additional equipment in a plant in the presence of uncertainties. This is especially true with designs of plants that are incapable of meeting any increase in demand. These aspects of the work are novel and an important contribution as such analysis is not available in the literature, to date. Three case studies that include a polygeneration plant and palm oil based integrated biorefinery are presented to demonstrate the proposed novel approach in a more descriptive manner. © 2014 American Chemical Society.
format text
author Kasivisvanathan, Harresh
Ubando, Aristotle T.
Ng, Denny K.S.
Tan, Raymond Girard R.
author_facet Kasivisvanathan, Harresh
Ubando, Aristotle T.
Ng, Denny K.S.
Tan, Raymond Girard R.
author_sort Kasivisvanathan, Harresh
title Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties
title_short Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties
title_full Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties
title_fullStr Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties
title_full_unstemmed Robust optimization for process synthesis and design of multifunctional energy systems with uncertainties
title_sort robust optimization for process synthesis and design of multifunctional energy systems with uncertainties
publisher Animo Repository
publishDate 2014
url https://animorepository.dlsu.edu.ph/faculty_research/3643
https://animorepository.dlsu.edu.ph/context/faculty_research/article/4645/type/native/viewcontent/ie401824j.html
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