Distributionally robust optimization for power trading of waste-to-energy plants under uncertainty

Hu, C; Liu, X; Lu, J; Wang, CH

Distributionally robust optimization for power trading of waste-to-energy plants under uncertainty

Hu, C Liu, X Lu, J

Wang, CH

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: Applied Energy, 2020, 276, pp. 115509-115509
Issue Date:: 2020-10-15

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Field	Value	Language
dc.contributor.author	Hu, C
dc.contributor.author	Liu, X
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732
dc.contributor.author	Wang, CH
dc.date.accessioned	2020-12-18T19:57:44Z
dc.date.available	2020-12-18T19:57:44Z
dc.date.issued	2020-10-15
dc.identifier.citation	Applied Energy, 2020, 276, pp. 115509-115509
dc.identifier.issn	0306-2619
dc.identifier.uri	http://hdl.handle.net/10453/144856
dc.description.abstract	© 2020 Waste-to-energy (WTE) plants are operated worldwide to address the management of municipal solid waste. Against this background, an increasing number of WTE plants serve as combined heat and power (CHP) producers that supply heat to the heating systems in local districts and trade electricity in the regional power markets. This paper studies a short-term operation planning problem of determining effective power trading strategies for WTE CHP plants that participate in day-ahead markets. A two-stage distributionally robust optimization (DRO) model is developed with the consideration of uncertain electricity prices, waste supply, and district heating demand. These different kinds of uncertainty are captured by an ambiguity set that contains a collection of possible probability distributions of the uncertain parameters. The two-stage DRO model seeks to ascertain a power trading strategy that maximizes the expected profit of a WTE CHP plant on a regular operating day under the worst-case distribution in the ambiguity set. As the DRO model is intractable, a solution method based on linear decision rule techniques is designed to reformulate the model as a tractable robust linear program. To test the applicability of the DRO model, a case study with real-world data is conducted. The computational results show that the two-stage DRO model can facilitate a WTE CHP plant in obtaining economical and robust power trading strategies for regular operating days in a day-ahead market. Furthermore, the impacts of the parameters in the ambiguity set on deriving robust power trading strategies for WTE CHP plants are investigated.
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Applied Energy
dc.relation.isbasedon	10.1016/j.apenergy.2020.115509
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	09 Engineering, 14 Economics
dc.subject.classification	Energy
dc.title	Distributionally robust optimization for power trading of waste-to-energy plants under uncertainty
dc.type	Journal Article
utslib.citation.volume	276
utslib.for	09 Engineering
utslib.for	14 Economics
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-12-18T19:57:27Z
pubs.publication-status	Published
pubs.volume	276

Abstract:

© 2020 Waste-to-energy (WTE) plants are operated worldwide to address the management of municipal solid waste. Against this background, an increasing number of WTE plants serve as combined heat and power (CHP) producers that supply heat to the heating systems in local districts and trade electricity in the regional power markets. This paper studies a short-term operation planning problem of determining effective power trading strategies for WTE CHP plants that participate in day-ahead markets. A two-stage distributionally robust optimization (DRO) model is developed with the consideration of uncertain electricity prices, waste supply, and district heating demand. These different kinds of uncertainty are captured by an ambiguity set that contains a collection of possible probability distributions of the uncertain parameters. The two-stage DRO model seeks to ascertain a power trading strategy that maximizes the expected profit of a WTE CHP plant on a regular operating day under the worst-case distribution in the ambiguity set. As the DRO model is intractable, a solution method based on linear decision rule techniques is designed to reformulate the model as a tractable robust linear program. To test the applicability of the DRO model, a case study with real-world data is conducted. The computational results show that the two-stage DRO model can facilitate a WTE CHP plant in obtaining economical and robust power trading strategies for regular operating days in a day-ahead market. Furthermore, the impacts of the parameters in the ambiguity set on deriving robust power trading strategies for WTE CHP plants are investigated.

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http://hdl.handle.net/10453/144856