Analysis of the applicability and results of swarm intelligence tools for the positioning of Energy Storage Systems

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dc.contributor.authorDivasson Jaureguibarria, Asier
dc.contributor.authorAranzabal Santamaria, Itxaso
dc.contributor.authorBedialauneta Landaribar, Miren Terese
dc.contributor.authorCastillo Aguirre, Paula
dc.date.accessioned2025-02-25T11:47:18Z
dc.date.available2025-02-25T11:47:18Z
dc.date.issued2024-12
dc.date.updated2025-02-25T11:47:18Z
dc.description.abstractThe integration of renewable energy is transforming traditional energy systems, blurring the distinction between producers and consumers and shifting towards a distributed grid network. This change demands innovative approaches to optimize Energy Storage Systems (ESS) and manage grid incidents efficiently, all without significant infrastructural changes. While optimization algorithms like Swarm Intelligence are gaining traction, critical aspects, such as worst-case scenario analysis in distribution networks, remain underexplored. This study addresses this gap by applying stochastic optimization techniques to determine the optimal placement and capacity of ESS in a medium voltage radial distribution system, using the IEEE 33-bus model. The findings highlight the importance of considering worst-case scenarios, offering a balanced evaluation of current methodologies. This research provides valuable insights for improving system flexibility and resilience, contributing to more effective and practical energy optimization strategies in real-world applications.en
dc.description.sponsorshipThis work is financially supported by the Basque Government,Spain under Grant IT1647-22 (ELEKTRIKER research group), by theMinisterio de Ciencia e Innovación, the Agencia Estatal de Inves-tigación and the European Union under Grant TED2021-129930A-I00 funded by MCIN/AEI/10.13039/501100011033 and by the ‘‘Euro-pean Union NextGenerationEU/PRTR’’ and under the Grant PID2021-125881OB-I00 funded by MICIU/AEI/10.13039/501100011033 and byERDF/EUen
dc.identifier.citationDivasson-J, A., Santamaria, I. A., Landaribar, M. T. B., & Aguirre, P. C. (2024). Analysis of the applicability and results of swarm intelligence tools for the positioning of Energy Storage Systems. International Journal of Electrical Power and Energy Systems, 163. https://doi.org/10.1016/J.IJEPES.2024.110343
dc.identifier.doi10.1016/J.IJEPES.2024.110343
dc.identifier.issn0142-0615
dc.identifier.urihttps://hdl.handle.net/20.500.14454/2374
dc.language.isoeng
dc.publisherElsevier Ltd
dc.rights© 2024 The Author(s)
dc.subject.otherDistribution systems
dc.subject.otherElectrical systems
dc.subject.otherEnergy storage systems
dc.subject.otherOptimization
dc.subject.otherStochastic algorithms
dc.titleAnalysis of the applicability and results of swarm intelligence tools for the positioning of Energy Storage Systemsen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.titleInternational Journal of Electrical Power and Energy Systems
oaire.citation.volume163
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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