A comparison of four approaches from stochastic programming for large-scale unit-commitment

In energy management, the unit-commitment problem deals with computing the most cost-efficient production schedule that meets customer load, while satisfying the operational constraints of the units. When the problem is large scale and/or much modelling detail is required, decomposition approaches a...

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Main Author:	Wim van Ackooij
Format:	article
Language:	EN
Published:	Elsevier 2017
Subjects:	49M37 65K05 90C15 Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95
Online Access:	https://doaj.org/article/022951c84a9848a19f51583b8bb53bc1
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id	oai:doaj.org-article:022951c84a9848a19f51583b8bb53bc1
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spelling	oai:doaj.org-article:022951c84a9848a19f51583b8bb53bc12021-12-02T05:00:59ZA comparison of four approaches from stochastic programming for large-scale unit-commitment2192-440610.1007/s13675-015-0051-xhttps://doaj.org/article/022951c84a9848a19f51583b8bb53bc12017-03-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2192440621000769https://doaj.org/toc/2192-4406In energy management, the unit-commitment problem deals with computing the most cost-efficient production schedule that meets customer load, while satisfying the operational constraints of the units. When the problem is large scale and/or much modelling detail is required, decomposition approaches are vital for solving this problem. The recent strong increase in intermittent, relative unforeseeable production has brought forth the need of examining methods from stochastic programming. In this paper we investigate and compare four such methods: probabilistically constrained programming, robust optimization and 2-stage stochastic and robust programming, on several large-scale instances from practice. The results show that the robust optimization approach is computationally the least costly but difficult to parameterize and has the highest recourse cost. The probabilistically constrained approach is second as computational cost is concerned and improves significantly the recourse cost functions with respect to the robust optimization approach. The 2-stage optimization approaches do poorly in terms of robustness, because the recourse decisions can compensate for this. Their total computational cost is highest. This leads to the insight that 2-stage flexibility and robustness can be (practically) orthogonal concepts.Wim van AckooijElsevierarticle49M3765K0590C15Applied mathematics. Quantitative methodsT57-57.97Electronic computers. Computer scienceQA75.5-76.95ENEURO Journal on Computational Optimization, Vol 5, Iss 1, Pp 119-147 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	49M37 65K05 90C15 Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95
spellingShingle	49M37 65K05 90C15 Applied mathematics. Quantitative methods T57-57.97 Electronic computers. Computer science QA75.5-76.95 Wim van Ackooij A comparison of four approaches from stochastic programming for large-scale unit-commitment
description	In energy management, the unit-commitment problem deals with computing the most cost-efficient production schedule that meets customer load, while satisfying the operational constraints of the units. When the problem is large scale and/or much modelling detail is required, decomposition approaches are vital for solving this problem. The recent strong increase in intermittent, relative unforeseeable production has brought forth the need of examining methods from stochastic programming. In this paper we investigate and compare four such methods: probabilistically constrained programming, robust optimization and 2-stage stochastic and robust programming, on several large-scale instances from practice. The results show that the robust optimization approach is computationally the least costly but difficult to parameterize and has the highest recourse cost. The probabilistically constrained approach is second as computational cost is concerned and improves significantly the recourse cost functions with respect to the robust optimization approach. The 2-stage optimization approaches do poorly in terms of robustness, because the recourse decisions can compensate for this. Their total computational cost is highest. This leads to the insight that 2-stage flexibility and robustness can be (practically) orthogonal concepts.
format	article
author	Wim van Ackooij
author_facet	Wim van Ackooij
author_sort	Wim van Ackooij
title	A comparison of four approaches from stochastic programming for large-scale unit-commitment
title_short	A comparison of four approaches from stochastic programming for large-scale unit-commitment
title_full	A comparison of four approaches from stochastic programming for large-scale unit-commitment
title_fullStr	A comparison of four approaches from stochastic programming for large-scale unit-commitment
title_full_unstemmed	A comparison of four approaches from stochastic programming for large-scale unit-commitment
title_sort	comparison of four approaches from stochastic programming for large-scale unit-commitment
publisher	Elsevier
publishDate	2017
url	https://doaj.org/article/022951c84a9848a19f51583b8bb53bc1
work_keys_str_mv	AT wimvanackooij acomparisonoffourapproachesfromstochasticprogrammingforlargescaleunitcommitment AT wimvanackooij comparisonoffourapproachesfromstochasticprogrammingforlargescaleunitcommitment
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A comparison of four approaches from stochastic programming for large-scale unit-commitment

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