Energy sector planning using multiple-index pinch analysis

Pinch analysis was initially developed as a methodology for optimizing energy efficiency in process plants. Applications of pinch analysis applications are based on common principles of using stream quantity and quality to determine optimal system targets. This initial targeting step identifies the...

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Main Authors: Patole, Mayuresh, Bandyopadhyay, Santanu, Foo, Dominic C.Y., Tan, Raymond Girard R.
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Published: Animo Repository 2017
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1655
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2654/type/native/viewcontent
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-26542021-07-14T00:29:48Z Energy sector planning using multiple-index pinch analysis Patole, Mayuresh Bandyopadhyay, Santanu Foo, Dominic C.Y. Tan, Raymond Girard R. Pinch analysis was initially developed as a methodology for optimizing energy efficiency in process plants. Applications of pinch analysis applications are based on common principles of using stream quantity and quality to determine optimal system targets. This initial targeting step identifies the pinch point, which then allows complex problems to be decomposed for the subsequent design of an optimal network using insights drawn from the targeting stage. One important class of pinch analysis problems is energy planning with footprint constraints, which began with the development of carbon emissions pinch analysis; in such problems, energy sources and demands are characterized by carbon footprint as the quality index. This methodology has been extended by using alternative quality indexes that measure different sustainability dimensions, such as water footprint, land footprint, emergy transformity, inoperability risk, energy return on investment and human fatalities. Pinch analysis variants still have the limitation of being able to use one quality index at a time, while previous attempts to develop pinch analysis methods using multiple indices have only been partially successful for special cases. In this work, a multiple-index pinch analysis method is developed by using an aggregate quality index, based on a weighted linear function of different quality indexes normally used in energy planning. The weights used to compute the aggregate index are determined via the analytic hierarchy process. A case study for Indian power sector is solved to illustrate how this approach allows multiple sustainability dimensions to be accounted for in energy planning. © 2017, Springer-Verlag Berlin Heidelberg. 2017-09-01T07:00:00Z text text/html https://animorepository.dlsu.edu.ph/faculty_research/1655 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2654/type/native/viewcontent Faculty Research Work Animo Repository Multiple criteria decision making Atmospheric carbon dioxide Energy development 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 Multiple criteria decision making
Atmospheric carbon dioxide
Energy development
Chemical Engineering
spellingShingle Multiple criteria decision making
Atmospheric carbon dioxide
Energy development
Chemical Engineering
Patole, Mayuresh
Bandyopadhyay, Santanu
Foo, Dominic C.Y.
Tan, Raymond Girard R.
Energy sector planning using multiple-index pinch analysis
description Pinch analysis was initially developed as a methodology for optimizing energy efficiency in process plants. Applications of pinch analysis applications are based on common principles of using stream quantity and quality to determine optimal system targets. This initial targeting step identifies the pinch point, which then allows complex problems to be decomposed for the subsequent design of an optimal network using insights drawn from the targeting stage. One important class of pinch analysis problems is energy planning with footprint constraints, which began with the development of carbon emissions pinch analysis; in such problems, energy sources and demands are characterized by carbon footprint as the quality index. This methodology has been extended by using alternative quality indexes that measure different sustainability dimensions, such as water footprint, land footprint, emergy transformity, inoperability risk, energy return on investment and human fatalities. Pinch analysis variants still have the limitation of being able to use one quality index at a time, while previous attempts to develop pinch analysis methods using multiple indices have only been partially successful for special cases. In this work, a multiple-index pinch analysis method is developed by using an aggregate quality index, based on a weighted linear function of different quality indexes normally used in energy planning. The weights used to compute the aggregate index are determined via the analytic hierarchy process. A case study for Indian power sector is solved to illustrate how this approach allows multiple sustainability dimensions to be accounted for in energy planning. © 2017, Springer-Verlag Berlin Heidelberg.
format text
author Patole, Mayuresh
Bandyopadhyay, Santanu
Foo, Dominic C.Y.
Tan, Raymond Girard R.
author_facet Patole, Mayuresh
Bandyopadhyay, Santanu
Foo, Dominic C.Y.
Tan, Raymond Girard R.
author_sort Patole, Mayuresh
title Energy sector planning using multiple-index pinch analysis
title_short Energy sector planning using multiple-index pinch analysis
title_full Energy sector planning using multiple-index pinch analysis
title_fullStr Energy sector planning using multiple-index pinch analysis
title_full_unstemmed Energy sector planning using multiple-index pinch analysis
title_sort energy sector planning using multiple-index pinch analysis
publisher Animo Repository
publishDate 2017
url https://animorepository.dlsu.edu.ph/faculty_research/1655
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2654/type/native/viewcontent
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