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 language | English (US) |
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Pages (from-to) | 382-393 |
Number of pages | 12 |
Journal | Computers and Chemical Engineering |
Volume | 84 |
DOIs | |
State | Published - Jan 4 2016 |
Externally published | Yes |
Bibliographical note
Funding Information:The authors gratefully acknowledge the financial support from the National Science Foundation under Grant No. 1159443 and from Praxair .
Publisher Copyright:
© 2015 Elsevier Ltd.
Keywords
- Demand side management
- Mixed-integer linear programming
- Power contracts
- Process networks
- Production scheduling