Journal
COMPUTERS & CHEMICAL ENGINEERING
Volume 86, Issue -, Pages 106-119Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2015.12.018
Keywords
Production scheduling; Demand response; Interruptible load; Adjustable robust optimization; Mixed-integer linear programming
Funding
- National Science Foundation [1159443]
- Praxair
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [1159443] Funding Source: National Science Foundation
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To ensure the stability of the power grid, backup capacities are called upon when electricity supply does not meet demand due to unexpected changes in the grid. As part of the demand response efforts in recent years, large electricity consumers are encouraged by financial incentives to provide such operating reserve in the form of load reduction capacities (interruptible load). However, a major challenge lies in the uncertainty that one does not know in advance when load reduction will be requested. In this work, we develop a scheduling model for continuous industrial processes providing interruptible load. An adjustable robust optimization approach, which incorporates recourse decisions using linear decision rules, is applied to model the uncertainty. The proposed model is applied to an illustrative example as well as a real-world air separation case. The results show the benefits from selling interruptible load and the value of considering recourse in the decision-making. (C) 2015 Elsevier Ltd. All rights reserved.
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