Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories

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 Pred...

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Main Authors:	Foo, Eddy Yi Shyh, Krishnan, Ashok, Patil, Bhagyesh V.
Other Authors:	School of Electrical and Electronic Engineering
Format:	Article
Language:	English
Published:	2018
Subjects:	Thermal Unit Hybrid Model Predictive Control DRNTU::Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/87832 http://hdl.handle.net/10220/46830
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-87832
record_format	dspace
spelling	sg-ntu-dr.10356-878322020-03-07T14:02:35Z Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories Foo, Eddy Yi Shyh Krishnan, Ashok Patil, Bhagyesh V. School of Electrical and Electronic Engineering Thermal Unit Hybrid Model Predictive Control DRNTU::Engineering::Electrical and electronic engineering 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. NRF (Natl Research Foundation, S’pore) Published version 2018-12-05T07:12:50Z 2019-12-06T16:50:24Z 2018-12-05T07:12:50Z 2019-12-06T16:50:24Z 2017 Journal Article 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 2405-8963 https://hdl.handle.net/10356/87832 http://hdl.handle.net/10220/46830 10.1016/j.ifacol.2017.08.1181 en IFAC-PapersOnLine © 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. 7 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	Thermal Unit Hybrid Model Predictive Control DRNTU::Engineering::Electrical and electronic engineering
spellingShingle	Thermal Unit Hybrid Model Predictive Control DRNTU::Engineering::Electrical and electronic engineering Foo, Eddy Yi Shyh Krishnan, Ashok Patil, Bhagyesh V. Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
description	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.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Foo, Eddy Yi Shyh Krishnan, Ashok Patil, Bhagyesh V.
format	Article
author	Foo, Eddy Yi Shyh Krishnan, Ashok Patil, Bhagyesh V.
author_sort	Foo, Eddy Yi Shyh
title	Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
title_short	Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
title_full	Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
title_fullStr	Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
title_full_unstemmed	Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
title_sort	hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories
publishDate	2018
url	https://hdl.handle.net/10356/87832 http://hdl.handle.net/10220/46830
_version_	1681041996416811008

Hybrid model predictive control framework for the thermal unit commitment problem including start-up and shutdown power trajectories

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