Robustness methodology to aid multiobjective decision making in the electricity generation capacity expansion problem to minimize cost and water withdrawal

Daniel Jornada and V. Jorge Leon

Applied Energy, 2016, vol. 162, issue C, 1089-1108

Abstract: This paper deals with the electricity generation capacity expansion problem to minimize cost and water withdrawal. Each solution prescribes locations and technologies for new power plants, and their designed capacities. A two-stage methodology is proposed to aid decision making by identifying the few alternatives from the many efficient solutions that are robust to uncertainties. The first stage finds solutions that are efficient in view of cost and water withdrawal objectives. The second stage finds the subset of first-stage solutions that are robust when the designed capacities of power plants are subjected to uncertainties at the time of their construction. The methodology is applied in a case study for the electrical grid in Texas, USA. The trade-off among technologies and locations, and the effect of uncertainty are considered to answer strategic questions for expansion planning. Experimental results suggest that the methodology prescribes locations, capacities and type of technologies for new power plants in Texas that tend to maintain their prescribed values of cost and water withdrawal when facing unforeseen implementation conditions, while satisfying the required generation capacity.

Keywords: Multiobjective optimization; Robustness; Electricity generation capacity expansion; Water-energy nexus (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261915013999
Full text for ScienceDirect subscribers only

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:eee:appene:v:162:y:2016:i:c:p:1089-1108

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2015.10.157

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().