dc.contributor.author | Löschenbrand, Markus | |
dc.date.accessioned | 2021-06-02T12:25:42Z | |
dc.date.available | 2021-06-02T12:25:42Z | |
dc.date.created | 2020-08-03T09:41:26Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 0142-0615 | |
dc.identifier.uri | https://hdl.handle.net/11250/2757419 | |
dc.description.abstract | This paper proposes a model to include investments in demand flexibility into traditional transmission expansion problems under uncertainty. To do so, a dynamic power flow model is proposed. The model is solved via applying a value function approximation in form of a neural network on the operational problem, allowing to yield a result for the non-convex investment problem. Additionally, robust sets are applied and linearized to deal with uncertainty and decrease computational complexity. In similar manner, Karush Kuhn Tucker conditions are used to transform a tri-level into a bi-level problem. Case studies for systems of varying complexity show the convergence of the algorithm as well as that flexible resources can be used as a cost-effective substitute for transmission lines in grid expansion. | en_US |
dc.language.iso | eng | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.subject | Robust optimization | en_US |
dc.subject | Transmission expansion planning | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Demand response | en_US |
dc.subject | Renewable generation | en_US |
dc.title | A transmission expansion model for dynamic operation of flexible demand | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | The Authors | en_US |
dc.source.volume | 124 | en_US |
dc.source.journal | International Journal of Electrical Power & Energy Systems | en_US |
dc.identifier.doi | 10.1016/j.ijepes.2020.106252 | |
dc.identifier.cristin | 1821240 | |
dc.relation.project | Norges forskningsråd: 257626 | en_US |
dc.relation.project | Norges forskningsråd: 255209 | en_US |
dc.source.articlenumber | 106252 | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |