Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units

The deep peak regulation of thermal units is an important measure for coping with significant wind power penetration. In this paper, based on interval optimization, a novel multi-objective unit commitment method is proposed considering the deep peak regulation of thermal units. In the proposed metho...

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Main Authors: Yinping Yang, Chao Qin, Yuan Zeng, Chengshan Wang
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Energies
Subjects:
Online Access:http://www.mdpi.com/1996-1073/12/5/922
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spelling doaj-7cab2dd29e8f46cebb7b128ff14b9c352020-11-24T22:20:19ZengMDPI AGEnergies1996-10732019-03-0112592210.3390/en12050922en12050922Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal UnitsYinping Yang0Chao Qin1Yuan Zeng2Chengshan Wang3Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaThe deep peak regulation of thermal units is an important measure for coping with significant wind power penetration. In this paper, based on interval optimization, a novel multi-objective unit commitment method is proposed considering the deep peak regulation of thermal units. In the proposed method, a thermal power cost model was developed to accurately determine the economic performance of three different peak regulation scenarios, particularly of the deep peak regulation scenario. The midpoint and width of the cost interval are simultaneously considered in the optimization process. The non-dominated sorting GA-II (NSGA-II) algorithm was incorporated into the model for a coordinated control of the midpoint and width of the obtained cost interval for further optimization. Considering that significant wind penetration results in greater nodal variations, the affine arithmetic was employed to solve nodal uncertainties, so that all system variations can be addressed. The method proposed in this paper was validated by a modified IEEE-39 bus system. The results showed that it serves as a useful tool for power dispatchers to obtain robust and economic solutions at different wind power prediction accuracies.http://www.mdpi.com/1996-1073/12/5/922deep peak regulationunit commitmentinterval numberoptimization methods
collection DOAJ
language English
format Article
sources DOAJ
author Yinping Yang
Chao Qin
Yuan Zeng
Chengshan Wang
spellingShingle Yinping Yang
Chao Qin
Yuan Zeng
Chengshan Wang
Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units
Energies
deep peak regulation
unit commitment
interval number
optimization methods
author_facet Yinping Yang
Chao Qin
Yuan Zeng
Chengshan Wang
author_sort Yinping Yang
title Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units
title_short Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units
title_full Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units
title_fullStr Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units
title_full_unstemmed Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units
title_sort interval optimization-based unit commitment for deep peak regulation of thermal units
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-03-01
description The deep peak regulation of thermal units is an important measure for coping with significant wind power penetration. In this paper, based on interval optimization, a novel multi-objective unit commitment method is proposed considering the deep peak regulation of thermal units. In the proposed method, a thermal power cost model was developed to accurately determine the economic performance of three different peak regulation scenarios, particularly of the deep peak regulation scenario. The midpoint and width of the cost interval are simultaneously considered in the optimization process. The non-dominated sorting GA-II (NSGA-II) algorithm was incorporated into the model for a coordinated control of the midpoint and width of the obtained cost interval for further optimization. Considering that significant wind penetration results in greater nodal variations, the affine arithmetic was employed to solve nodal uncertainties, so that all system variations can be addressed. The method proposed in this paper was validated by a modified IEEE-39 bus system. The results showed that it serves as a useful tool for power dispatchers to obtain robust and economic solutions at different wind power prediction accuracies.
topic deep peak regulation
unit commitment
interval number
optimization methods
url http://www.mdpi.com/1996-1073/12/5/922
work_keys_str_mv AT yinpingyang intervaloptimizationbasedunitcommitmentfordeeppeakregulationofthermalunits
AT chaoqin intervaloptimizationbasedunitcommitmentfordeeppeakregulationofthermalunits
AT yuanzeng intervaloptimizationbasedunitcommitmentfordeeppeakregulationofthermalunits
AT chengshanwang intervaloptimizationbasedunitcommitmentfordeeppeakregulationofthermalunits
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