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dc.contributor.authorAlic, Asja
dc.contributor.authorSchäffer, Linn Emelie
dc.contributor.authorToffolon, Marco
dc.contributor.authorVincenzo, Trovato
dc.date.accessioned2024-03-20T11:52:40Z
dc.date.available2024-03-20T11:52:40Z
dc.date.created2023-10-11T14:34:12Z
dc.date.issued2023
dc.identifier.issn1868-3967
dc.identifier.urihttps://hdl.handle.net/11250/3123367
dc.description.abstractThe paper proposes a novel medium-term scheduling model for a hydropower system composed by a pumped storage hydropower plant connected to a traditional hydropower plant subject to three types of environmental constraints; these deal with the maximum water abstraction from the reservoir thought the turbines and through the pump for energy production, the minimum environmental water flow and the ramping capabilities of water volumes inside the system’s reservoirs. The scheduling problem is formulated for a planning horizon of 1 year with weekly decision stages. The methodology to determine the optimal operation of the plant is based on a stochastic dynamic programming algorithm which allows for an accurate representation of the uncertainties associated to the water inflows and energy prices. Moreover, it facilitates the handling of the non-convex characteristic of the state-dependent constraint on maximum water abstraction from the reservoir. The model is applied to the case of a real hydropower system based on a cascaded watercourse with two conventional hydropower plants in south of Norway to assess the economic benefits of having a pumping unit and the technical impact of the above-mentioned environmental constraints. Furthermore, this work proposes a methodology to analyze the optimal operation of the hydropower system, computed for different temporal resolutions, in order to investigate the techno-economic impact of the constraints involving dependencies on the states of the system, the different environmental constraints and other seasonal effects on the accuracy and the applicability of medium-term scheduling models. Further case studies assess the computational burden and the precision of the results when adopting a finer discretization of the state variables of the dynamic-programming-based methodology. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.en_US
dc.description.abstractOptimal price-based scheduling of a pumped-storage hydropower plant considering environmental constraintsen_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.titleOptimal price-based scheduling of a pumped-storage hydropower plant considering environmental constraintsen_US
dc.title.alternativeOptimal price-based scheduling of a pumped-storage hydropower plant considering environmental constraintsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.journalEnergy Systems, Springer Verlagen_US
dc.identifier.doi10.1007/s12667-023-00614-y
dc.identifier.cristin2183814
dc.relation.projectNorges forskningsråd: 320794en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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