Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system

dc.contributor.authorVahid-Ghavidel, M.
dc.contributor.authorShafie-khah, M.
dc.contributor.authorJavadi, M.S.
dc.contributor.authorSantos, Sérgio F.
dc.contributor.authorQuijano, D.A.
dc.contributor.authorCatalão, J.P.S.
dc.date.accessioned2023-07-17T15:48:28Z
dc.date.available2023-07-17T15:48:28Z
dc.date.issued2023-02-15
dc.description.abstractThe optimal management of distributed energy resources (DERs) and renewable-based generation in multi-energy systems (MESs) is crucial as it is expected that these entities will be the backbone of future energy systems. To optimally manage these numerous and diverse entities, an aggregator is required. This paper proposes the self-scheduling of a DER aggregator through a hybrid Info-gap Decision Theory (IGDT)-stochastic approach in an MES. In this approach, there are several renewable energy resources such as wind and photovoltaic (PV) units as well as multiple DERs, including combined heat and power (CHP) units, and auxiliary boilers (ABs). The approach also considers an EV parking lot and thermal energy storage systems (TESs). Moreover, two demand response (DR) programs from both price-based and incentive-based categories are employed in the microgrid to provide flexibility for the participants. The uncertainty in the generation is addressed through stochastic programming. At the same time, the uncertainty posed by the energy market prices is managed through the application of the IGDT method. A major goal of this model is to choose the risk measure based on the nature and characteristics of the uncertain parameters in the MES. Additionally, the behavior of the risk-averse and risk-seeking decision-makers is also studied. In the first stage, the sole-stochastic results are presented and then, the hybrid stochastic-IGDT results for both risk-averse and risk-seeker decision-makers are discussed. The proposed problem is simulated on the modified IEEE 15-bus system to demonstrate the effectiveness and usefulness of the technique.pt_PT
dc.identifier.citationVahid-Ghavidel, M., Shafie-khah, M., Javadi, M. S., Santos, S. F., Gough, M., Quijano, D. A., & Catalão, J. P. S. (2023). Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system. Energy, 265(126289), 1-13. https://doi.org/10.1016/j.energy.2022.126289. Repositório Institucional UPT. http://hdl.handle.net/11328/4952pt_PT
dc.identifier.doihttps://doi.org/10.1016/j.energy.2022.126289pt_PT
dc.identifier.issn0360-5442
dc.identifier.urihttp://hdl.handle.net/11328/4952
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationM. Vahid-Ghavidel acknowledges the support of FCT through the Ph. D. Scholarship with reference number 2020.08822.BD. M. Gough acknowledges the support of FCT through the Ph.D. Scholarship with reference number UI/BD/152279/2021. M. S. Javadi acknowledges the support of FCT for his contract funding provided through 2021.01052. CEECIND. Also, J.P.S. Catalao ˜ acknowledges the support of FEDER through COMPETE 2020 and FCT under POCI-010145-FEDER-029803 (02/SAICT/2017).pt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0360544222031759pt_PT
dc.rightsopen accesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectDemand responsept_PT
dc.subjectDistributed energy resourcespt_PT
dc.subjectMicrogridpt_PT
dc.subjectMulti-energy systempt_PT
dc.subjectStochastic programmingpt_PT
dc.titleHybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy systempt_PT
dc.typejournal articlept_PT
degois.publication.firstPage1pt_PT
degois.publication.issue126289pt_PT
degois.publication.lastPage13pt_PT
degois.publication.titleEnergypt_PT
degois.publication.volume265pt_PT
dspace.entity.typePublicationen
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