An MILP framework for optimizing demand response operation of air separation units
Morgan T. Kelley,
Richard C. Pattison,
Ross Baldick and
Michael Baldea
Applied Energy, 2018, vol. 222, issue C, 966 pages
Abstract:
Peaks in renewable electricity generation and consumer demand are desynchronized in time, posing a challenge for grid operators. Industrial demand response (DR) has emerged as a candidate for mitigating this variability. In this paper, we demonstrate the application of DR to an air separation unit (ASU). We develop a novel optimal production scheduling framework that accounts for day-ahead electricity prices to modulate the grid load presented by the plant. We account for the dynamics of the plant using a novel dynamic modeling strategy, which allows us to formulate the corresponding optimization problem as a mixed integer linear program (MILP). Further, we present a new relaxation scheme that affords fast solutions of this MILP. Extensive simulation results show significant reductions in operating costs (that benefit the plant) and reductions in peak power demand (that benefit the grid).
Keywords: Demand response; Air separation; Production scheduling; Lagrangian relaxation (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261917318524
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:222:y:2018:i:c:p:951-966
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.2017.12.127
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 ().