 A real-time decision model for industrial load management in a smart gridMengmeng Yu, Renzhi Lu and Seung Ho Hong Applied Energy, 2016, vol. 183, issue C, 1488-1497 Abstract: The potential impacts of evolving industrial load management into demand response (DR) programs have been widely acknowledged. This paper proposes a real-time decision model for the load management of an industrial manufacturing process in the face of ever-changing real-time prices (RTPs). Due to the inherent dependence between consecutive tasks in a manufacturing process, the decision model must take future load management into consideration. The challenge lies in the uncertainty that future RTPs cannot be known in advance. In view of this, robust optimization was adopted to deal with future price uncertainties, such that the proposed model is able to make timely decisions for industrial load control when receiving the RTP for the current time slot, while considering load scheduling in future time slots. The case study was conducted on a steel powder manufacturing process; simulation results validated the effectiveness of the proposed real-time decision approach from various perspectives. Keywords: Industrial manufacturing process; Real-time price; Timely decision; Robust optimization; Demand response (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:183:y:2016:i:c:p:1488-1497 Ordering information: This journal article can be ordered from DOI: 10.1016/j.apenergy.2016.09.021 Access Statistics for this article Applied Energy is currently edited by J. Yan More articles in Applied Energy from Elsevier |
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