Data set and model code on the optimal operating state of a negative emission polygeneration system

This article contains the data set and model code for the negative emission polygeneration system described in Tan et al. (2019). The data was generated utilizing an optimization model implemented in LINGO 18.0 and includes information on the operating state of each process unit in the system. The m...

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Main Authors: Aviso, Kathleen B., Tan, Raymond Girard R., Foo, Dominic C. Y., Lee, Jui Yuan, Ubando, Aristotle T.
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Published: Animo Repository 2020
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-34832021-10-06T08:39:37Z Data set and model code on the optimal operating state of a negative emission polygeneration system Aviso, Kathleen B. Tan, Raymond Girard R. Foo, Dominic C. Y. Lee, Jui Yuan Ubando, Aristotle T. This article contains the data set and model code for the negative emission polygeneration system described in Tan et al. (2019). The data was generated utilizing an optimization model implemented in LINGO 18.0 and includes information on the operating state of each process unit in the system. The maximum annual profit of the system was determined at different carbon footprint targets. The data set and model code can be utilized for further analysis on the interdependence between the process units of this polygeneration system, its operational and environmental performance, and the potential impact of integrating new process units into the network. © 2020 The Author(s) 2020-04-01T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/2484 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3483/type/native/viewcontent Faculty Research Work Animo Repository Carbon taxes Carbon dioxide mitigation Saline water conversion Polygeneration systems Chemical Engineering
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 Carbon taxes
Carbon dioxide mitigation
Saline water conversion
Polygeneration systems
Chemical Engineering
spellingShingle Carbon taxes
Carbon dioxide mitigation
Saline water conversion
Polygeneration systems
Chemical Engineering
Aviso, Kathleen B.
Tan, Raymond Girard R.
Foo, Dominic C. Y.
Lee, Jui Yuan
Ubando, Aristotle T.
Data set and model code on the optimal operating state of a negative emission polygeneration system
description This article contains the data set and model code for the negative emission polygeneration system described in Tan et al. (2019). The data was generated utilizing an optimization model implemented in LINGO 18.0 and includes information on the operating state of each process unit in the system. The maximum annual profit of the system was determined at different carbon footprint targets. The data set and model code can be utilized for further analysis on the interdependence between the process units of this polygeneration system, its operational and environmental performance, and the potential impact of integrating new process units into the network. © 2020 The Author(s)
format text
author Aviso, Kathleen B.
Tan, Raymond Girard R.
Foo, Dominic C. Y.
Lee, Jui Yuan
Ubando, Aristotle T.
author_facet Aviso, Kathleen B.
Tan, Raymond Girard R.
Foo, Dominic C. Y.
Lee, Jui Yuan
Ubando, Aristotle T.
author_sort Aviso, Kathleen B.
title Data set and model code on the optimal operating state of a negative emission polygeneration system
title_short Data set and model code on the optimal operating state of a negative emission polygeneration system
title_full Data set and model code on the optimal operating state of a negative emission polygeneration system
title_fullStr Data set and model code on the optimal operating state of a negative emission polygeneration system
title_full_unstemmed Data set and model code on the optimal operating state of a negative emission polygeneration system
title_sort data set and model code on the optimal operating state of a negative emission polygeneration system
publisher Animo Repository
publishDate 2020
url https://animorepository.dlsu.edu.ph/faculty_research/2484
https://animorepository.dlsu.edu.ph/context/faculty_research/article/3483/type/native/viewcontent
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