Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm

Simple item page
dc.contributor.authorSubramanian, Avinash S. R.en
dc.contributor.authorKannan, Rohiten
dc.contributor.authorHoltorf, Flemmingen
dc.contributor.authorAdams II, Thomas A.en
dc.contributor.authorGundersen, Trulsen
dc.contributor.authorBarton, Paul I.en
dc.date.accessioned2025-02-18T13:14:17Zen
dc.date.available2025-02-18T13:14:17Zen
dc.date.issued2023-12-01en
dc.description.abstractMarket uncertainties motivate the development of flexible polygeneration systems that are able to adjust operating conditions to favor production of the most profitable product portfolio. However, this operational flexibility comes at the cost of higher capital expenditure. A scenario-based two-stage stochastic nonconvex Mixed-Integer Nonlinear Programming (MINLP) approach lends itself naturally to optimizing these trade-offs. This work studies the optimal design and operation under uncertainty of a hybrid feedstock flexible polygeneration system producing electricity, methanol, dimethyl ether, olefins or liquefied (synthetic) natural gas. A recently developed C++ based software framework (named GOSSIP) is used for modeling the optimization problem as well as its efficient solution using the Nonconvex Generalized Benders Decomposition (NGBD) algorithm. Two different cases are studied: The first uses estimates of the means and variances of the uncertain parameters from historical data, whereas the second assesses the impact of increased uncertain parameter volatility. The value of implementing flexible designs characterized by the value of the stochastic solution (VSS) is in the range of 260–405 M$ for a scale of approximately 893 MW of thermal input. Increased price volatility around the same mean results in higher expected net present value and VSS as operational flexibility allows for asymmetric exploitation of price peaks.en
dc.description.versionPublished versionen
dc.format.extent11 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifierARTN 129222 (Article number)en
dc.identifier.doihttps://doi.org/10.1016/j.energy.2023.129222en
dc.identifier.eissn1873-6785en
dc.identifier.issn0360-5442en
dc.identifier.orcidKannan, Rohit [0000-0002-7963-7682]en
dc.identifier.urihttps://hdl.handle.net/10919/124624en
dc.identifier.volume284en
dc.language.isoenen
dc.publisherPergamon-Elsevieren
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectPolygeneration systemen
dc.subjectWaste-to-energyen
dc.subjectStochastic programmingen
dc.subjectDecomposition algorithmen
dc.subjectWaste tireen
dc.subjectOptimization under uncertaintyen
dc.titleOptimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithmen
dc.title.serialEnergyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dc.type.otherJournalen
pubs.organisational-groupVirginia Techen
pubs.organisational-groupVirginia Tech/Engineeringen
pubs.organisational-groupVirginia Tech/Engineering/Industrial and Systems Engineeringen
pubs.organisational-groupVirginia Tech/All T&R Facultyen
pubs.organisational-groupVirginia Tech/Engineering/COE T&R Facultyen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm.pdf
Size:
3.28 MB
Format:
Adobe Portable Document Format
Description:
Published version
Download
License bundle
Now showing 1 - 1 of 1
Name:
license.txt
Size:
1.5 KB
Format:
Plain Text
Description:
Download

Collections

All Faculty Deposits
Scholarly Works, Industrial and Systems Engineering