Optimising the water-energy nexus over process and product networks

Daniel J. Garcia, Fengqi You*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations


Producing renewable fuels from biomass has been proposed as a means to lower our carbon footprint and help establish sustainable industrial processes. However, key questions must be answered about these bio-based processes before they can truly be considered a promising alternative. While economics and emissions of these processes have been studied and optimised at length, the critical component of water consumption must be considered, as future water scarcity has been identified as a key challenge. This work compiles a network of hundreds of bioconversion technologies and aims to optimise them over the objectives of production cost and water consumption. The water efficiency of energy (WEE) is also calculated. Water consumption is considered from biomass cultivation to processing, providing a better glimpse into the true consumption of this resource throughout the value chain. A multiobjective MINLP model is formulated as well as an MILP-based branch and refine algorithm to boost solving efficiency. An illustrative case study using a variety of feedstocks under demand of primary fuel products (ethanol, diesel, and gasoline) is presented. The water consumption of the Pareto-optimal solutions ranged from 54.9·× 106 L/y to 215,121·× 106 L/y with corresponding production costs of 251·× 106 $/y to -240.8·× 106 $/y. The WEE ranged from 0.04 L/MJ to 111.3 L/MJ. The branch and refine algorithms were shown to be orders of magnitude more efficient than directly solving the original MINLP problem with general purpose solvers.

Original languageEnglish (US)
Title of host publicationChemical Engineering Transactions
PublisherItalian Association of Chemical Engineering - AIDIC
Number of pages6
ISBN (Electronic)9788895608365
StatePublished - Oct 1 2015

ASJC Scopus subject areas

  • General Chemical Engineering


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