Optimized Self-Scheduling of a Hydrogen-Based Virtual Power Plant in the Day-Ahead Electricity Market

dc.contributor.authorÁlvarez Quispe, Erik Franciscoes-ES
dc.date.accessioned2025-09-16T12:10:38Z
dc.date.available2025-09-16T12:10:38Z
dc.date.issued2026-09-17
dc.description.abstractThis study presents an optimisation model for the self-scheduling of a hydrogen-based virtual power plant (H2-VPP) in the day-ahead electricity market. The model strategically integrates renewable energy sources, battery storage, electrolysers and hydrogen storage to maximise operational efficiency and economic performance. By optimising the interaction between electricity and hydrogen networks, it enables better resource management and increased use of renewable energy. A case study evaluates different system configurations, highlighting the impact of battery storage and hydrogen tanks on cost reduction. The results show that excluding battery storage increases costs by up to 87%, while excluding hydrogen storage increases costs by up to 153%. These findings underline the critical role of storage technologies in increasing flexibility, minimising electricity purchases and improving market competitiveness. The proposed framework supports the development of hydrogen-based VPPs, contributing to a more efficient and resilient energy transition.en-GB
dc.description.versioninfo:eu-repo/semantics/draft
dc.format.mimetypeapplication/pdfes_ES
dc.identifier.urihttp://hdl.handle.net/11531/104211
dc.keywordsElectrolyzer Scheduling; Electricity Markets; Programming, Mixed-Integeren-GB
dc.language.isoen-GB
dc.rightses_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.uries_ES
dc.titleOptimized Self-Scheduling of a Hydrogen-Based Virtual Power Plant in the Day-Ahead Electricity Market
dc.typeinfo:eu-repo/semantics/workingPaper

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