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Article: Joint planning of energy storage and transmission for wind energy generation

TitleJoint planning of energy storage and transmission for wind energy generation
Authors
KeywordsFacility Location
Energy Storage
Wind Energy
Infrastructure Planning
Issue Date2015
Citation
Operations Research, 2015, v. 63, n. 6, p. 1280-1293 How to Cite?
Abstract© 2015 INFORMS. Regions with abundant wind resources usually have no ready access to the existing electric grid. However, building transmission lines that instantaneously deliver all geographically distributed wind energy can be costly. Energy storage (ES) systems can help reduce the cost of bridging wind farms and grids and mitigate the intermittency of wind outputs. In this paper, we propose models of transmission network planning with colocation of ES systems. Our models determine the sizes and sites of ES systems as well as the associated topology and capacity of the transmission network under the feed-in-tariff policy instrument. We first formulate a location model as a mixed-integer second-order-conic program to solve for the ES-transmission network design with uncapacitated storage. Then we propose a method to choose ES sizes by deriving a closed-form upper bound. The major insight is that, in most cases, using even small-sized ES systems can significantly reduce the total expected cost, but their marginal values diminish faster than those of the transmission lines as their capacities expand. Despite uncertainties in climate, technologies, and construction costs, the cost-efficient infrastructure layout is remarkably robust. We also identify the major bottleneck cost factors for different forms of ES technologies.
Persistent Identifierhttp://hdl.handle.net/10722/296116
ISSN
2023 Impact Factor: 2.2
2023 SCImago Journal Rankings: 2.848
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorQi, Wei-
dc.contributor.authorLiang, Yong-
dc.contributor.authorShen, Zuo Jun Max-
dc.date.accessioned2021-02-11T04:52:52Z-
dc.date.available2021-02-11T04:52:52Z-
dc.date.issued2015-
dc.identifier.citationOperations Research, 2015, v. 63, n. 6, p. 1280-1293-
dc.identifier.issn0030-364X-
dc.identifier.urihttp://hdl.handle.net/10722/296116-
dc.description.abstract© 2015 INFORMS. Regions with abundant wind resources usually have no ready access to the existing electric grid. However, building transmission lines that instantaneously deliver all geographically distributed wind energy can be costly. Energy storage (ES) systems can help reduce the cost of bridging wind farms and grids and mitigate the intermittency of wind outputs. In this paper, we propose models of transmission network planning with colocation of ES systems. Our models determine the sizes and sites of ES systems as well as the associated topology and capacity of the transmission network under the feed-in-tariff policy instrument. We first formulate a location model as a mixed-integer second-order-conic program to solve for the ES-transmission network design with uncapacitated storage. Then we propose a method to choose ES sizes by deriving a closed-form upper bound. The major insight is that, in most cases, using even small-sized ES systems can significantly reduce the total expected cost, but their marginal values diminish faster than those of the transmission lines as their capacities expand. Despite uncertainties in climate, technologies, and construction costs, the cost-efficient infrastructure layout is remarkably robust. We also identify the major bottleneck cost factors for different forms of ES technologies.-
dc.languageeng-
dc.relation.ispartofOperations Research-
dc.subjectFacility Location-
dc.subjectEnergy Storage-
dc.subjectWind Energy-
dc.subjectInfrastructure Planning-
dc.titleJoint planning of energy storage and transmission for wind energy generation-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1287/opre.2015.1444-
dc.identifier.scopuseid_2-s2.0-84955131134-
dc.identifier.volume63-
dc.identifier.issue6-
dc.identifier.spage1280-
dc.identifier.epage1293-
dc.identifier.eissn1526-5463-
dc.identifier.isiWOS:000367833500004-
dc.identifier.issnl0030-364X-

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