Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/87832
Title: Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
Authors: Foo, Eddy Yi Shyh
Krishnan, Ashok
Patil, Bhagyesh V.
Keywords: Thermal Unit
Hybrid Model Predictive Control
DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2017
Source: Krishnan, A., Foo, E. Y. S., & Patil, B. V. (2017). Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories. IFAC-PapersOnLine, 50(1), 9329-9335. doi:10.1016/j.ifacol.2017.08.1181
Series/Report no.: IFAC-PapersOnLine
Abstract: This paper presents a generalized mixed logical dynamical (MLD) approach for modelling thermal units. A self-scheduling problem is formulated for a thermal unit including an accurate model of its start-up and shutdown power trajectories. This optimal self-scheduling problem is solved in a Model Predictive Control (MPC) framework. The problem formulation considers all the relevant constraints associated with the scheduling of thermal units. The efficacy of the proposed MLD approach is demonstrated through simulation results. These results are extended to a system of 5 units and the optimal scheduling problem is formulated and solved.
URI: https://hdl.handle.net/10356/87832
http://hdl.handle.net/10220/46830
ISSN: 2405-8963
DOI: http://dx.doi.org/10.1016/j.ifacol.2017.08.1181
Rights: © 2017 IFAC (International Federation of Automatic Control). This paper was published in IFAC-PapersOnLine and is made available as an electronic reprint (preprint) with permission of IFAC (International Federation of Automatic Control). The published version is available at: [http://dx.doi.org/10.1016/j.ifacol.2017.08.1181]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
metadata.item.grantfulltext: open
metadata.item.fulltext: With Fulltext
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