A Novel Formulation for the Energy Storage Scheduling Problem in Solar Self-consumption Systems

Simple item page
dc.contributor.authorLloréns, Icíar
dc.contributor.authorAlonso, Ricardo
dc.contributor.authorGil-López, Sergio
dc.contributor.authorRiaño, Sandra
dc.contributor.authorDel Ser, Javier
dc.contributor.editorHerrero, Álvaro
dc.contributor.editorCambra, Carlos
dc.contributor.editorUrda, Daniel
dc.contributor.editorSedano, Javier
dc.contributor.editorQuintián, Héctor
dc.contributor.editorCorchado, Emilio
dc.contributor.institutionSISTEMAS FOTOVOLTAICOS
dc.contributor.institutionIA
dc.date.accessioned2024-07-24T11:51:15Z
dc.date.available2024-07-24T11:51:15Z
dc.date.issued2021
dc.descriptionPublisher Copyright: © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
dc.description.abstractEnergy storage systems are key components to increase photovoltaic (PV) self-consumption profitability. Indeed, they allow for the intermittency dampening of the PV production so as to adequately cover end-users’ consumption. Given that in most grid-connected PV systems electricity prices are variable, an informed battery scheduling can significantly decrease energy costs. Moreover, energy storage systems can cover consumption peaks to enable contracted power reduction and hence additional savings in electricity bill. This work elaborates on a scalable and flexible optimization system based on production and load forecasting as a Model Predictive Control (MPC) for battery scheduling that aims at minimizing energy costs for consumers. The system provides a 24-hour-ahead battery plan that reduces purchase cost from grid, extends the battery lifetime and guarantees purchases below the maximum contracted power. The formulated problem is solved by means of a MINLP solver and several evolutionary algorithms. Results obtained by these optimization algorithms over real data are promising in terms of cost savings within Spanish electricity market, particularly when compared to the results rendered by other methods from the state of the art. We end by outlying several research directions rooted on the findings reported in this study.en
dc.description.sponsorshipAcknowledgments. The work herein described has received funding from the EU’s Horizon 2020 research and innovation program under grant agreement No 691768. Javier Del Ser receives funding support from the Consolidated Research Group MATHMODE (IT1294-19) granted by the Department of Education of the Basque Government. The work herein described has received funding from the EU?s Horizon 2020 research and innovation program under grant agreement No 691768. Javier Del Ser receives funding support from the Consolidated Research Group MATHMODE (IT1294-19) granted by the Department of Education of the Basque Government.
dc.description.statusPeer reviewed
dc.format.extent12
dc.identifier.citationLloréns , I , Alonso , R , Gil-López , S , Riaño , S & Del Ser , J 2021 , A Novel Formulation for the Energy Storage Scheduling Problem in Solar Self-consumption Systems . in Á Herrero , C Cambra , D Urda , J Sedano , H Quintián & E Corchado (eds) , 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020 . Advances in Intelligent Systems and Computing , vol. 1268 AISC , Springer Science and Business Media Deutschland GmbH , pp. 67-78 , 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020 , Burgos , Spain , 16/09/20 . https://doi.org/10.1007/978-3-030-57802-2_7
dc.identifier.citationconference
dc.identifier.doi10.1007/978-3-030-57802-2_7
dc.identifier.isbn9783030578015
dc.identifier.issn2194-5357
dc.identifier.urihttps://hdl.handle.net/11556/2062
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85091295431&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartof15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computing
dc.relation.projectIDDepartment of Education of the Basque Government
dc.relation.projectIDEU?s Horizon 2020 research and innovation program
dc.relation.projectIDEU’s Horizon 2020 research and innovation program, IT1294-19-691768
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsEvolutionary algorithms
dc.subject.keywordsMINLP optimization
dc.subject.keywordsModel Predictive Control (MPC)
dc.subject.keywordsRenewable energy integration
dc.subject.keywordsSolar energy
dc.subject.keywordsControl and Systems Engineering
dc.subject.keywordsGeneral Computer Science
dc.subject.keywordsSDG 7 - Affordable and Clean Energy
dc.titleA Novel Formulation for the Energy Storage Scheduling Problem in Solar Self-consumption Systemsen
dc.typeconference output
Files