A discrete-time scheduling model for continuous power-intensive process networks with various power contracts

Qi Zhang, Arul Sundaramoorthy, Ignacio E. Grossmann, Jose M. Pinto

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

Increased volatility in electricity prices and new emerging demand side management opportunities call for efficient tools for the optimal operation of power-intensive processes. In this work, a general discrete-time model is proposed for the scheduling of power-intensive process networks with various power contracts. The proposed model consists of a network of processes represented by Convex Region Surrogate models that are incorporated in a mode-based scheduling formulation, for which a block contract model is considered that allows the modeling of a large variety of commonly used power contracts. The resulting mixed-integer linear programming model is applied to an illustrative example as well as to a real-world industrial test case. The results demonstrate the model's capability in representing the operational flexibility in a process network and different electricity pricing structures. Moreover, because of its computational efficiency, the model holds much promise for its use in a real industrial setting.

Original languageEnglish (US)
Pages (from-to)382-393
Number of pages12
JournalComputers and Chemical Engineering
Volume84
DOIs
StatePublished - Jan 4 2016
Externally publishedYes

Bibliographical note

Funding Information:
The authors gratefully acknowledge the financial support from the National Science Foundation under Grant No. 1159443 and from Praxair .

Keywords

  • Demand side management
  • Mixed-integer linear programming
  • Power contracts
  • Process networks
  • Production scheduling

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