The Food-Energy-Water Nexus in Sustainable Energy Systems Solutions

Marcello Di Martino (), R. Cory Allen () and Efstratios N. Pistikopoulos ()
Additional contact information
Marcello Di Martino: Texas A&M University
R. Cory Allen: Texas A&M University
Efstratios N. Pistikopoulos: Texas A&M University

A chapter in Handbook of Smart Energy Systems, 2023, pp 2967-2986 from Springer

Abstract: Abstract Sustainable energy system solutions often require systematic consideration of water and land resources. Such a strategy leads to the food-energy-water nexus (FEWN) problem, which postulates that food, energy and water systems have to be analyzed holistically. The FEWN has received an increased interest in literature since it enables the derivation of sustainable solutions of challenges which are the result of an increasing global population and energy demand, together with decreasing water resources. Process Systems Engineering (PSE) can be utilized to this end since PSE is uniquely positioned to address sustainability challenges due to its systematic and qualitative nature. This work presents recent advancements of PSE methods applied to the FEWN. Therefore, the general problem statement, and challenges, together with state-of-the-art methods of the nexus is identified with a focus on mathematical modeling and optimization. A key challenge is the multiscale nature of the problem regarding the spatial and temporal dimensions, where AI/machine learning data-driven methods are frequently employed. Future research directions, modeling gaps, and open problems are also briefly highlighted.

Keywords: Food-energy-water nexus; Mathematical modeling and optimization; Mixed-integer programming; Multiscale engineering; Sustainability (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-97940-9_168

Ordering information: This item can be ordered from
http://www.springer.com/9783030979409

DOI: 10.1007/978-3-030-97940-9_168

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().