A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems

Aiying Rong; Henri Hakonen; Risto Lahdelma

doi:10.1016/j.enconman.2008.12.003

A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems

Aiying Rong, Henri Hakonen, Risto Lahdelma

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

This paper addresses the unit commitment (UC) in multi-period combined heat and power (CHP) production planning under the deregulated power market. In CHP plants (units), generation of heat and power follows joint characteristics, which implies that it is difficult to determine the relative cost efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained.

Original language	English
Journal	Energy Conversion and Management
Volume	50
Issue number	4
Pages (from-to)	1108-1115
ISSN	0196-8904
DOIs	https://doi.org/10.1016/j.enconman.2008.12.003
Publication status	Published - 2009

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title = "A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems",

abstract = "This paper addresses the unit commitment (UC) in multi-period combined heat and power (CHP) production planning under the deregulated power market. In CHP plants (units), generation of heat and power follows joint characteristics, which implies that it is difficult to determine the relative cost efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained.",

author = "Aiying Rong and Henri Hakonen and Risto Lahdelma",

year = "2009",

doi = "10.1016/j.enconman.2008.12.003",

language = "English",

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journal = "Energy Conversion and Management",

issn = "0196-8904",

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TY - JOUR

T1 - A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems

AU - Rong, Aiying

AU - Hakonen, Henri

AU - Lahdelma, Risto

PY - 2009

Y1 - 2009

N2 - This paper addresses the unit commitment (UC) in multi-period combined heat and power (CHP) production planning under the deregulated power market. In CHP plants (units), generation of heat and power follows joint characteristics, which implies that it is difficult to determine the relative cost efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained.

AB - This paper addresses the unit commitment (UC) in multi-period combined heat and power (CHP) production planning under the deregulated power market. In CHP plants (units), generation of heat and power follows joint characteristics, which implies that it is difficult to determine the relative cost efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained.

U2 - 10.1016/j.enconman.2008.12.003

DO - 10.1016/j.enconman.2008.12.003

M3 - Journal article

VL - 50

SP - 1108

EP - 1115

JO - Energy Conversion and Management

JF - Energy Conversion and Management

SN - 0196-8904

IS - 4

ER -