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

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Álvarez Quispe, Erik Francisco
Sánchez Martín, Pedro
Ramos Galán, Andrés
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info:eu-repo/semantics/draft
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Abstract
 
 
This 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.
 
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http://hdl.handle.net/11531/104954
Optimized Self-Scheduling of a Hydrogen-Based Virtual Power Plant in the Day-Ahead Electricity Market
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Electrolyzer Scheduling; Electricity Markets; Programming, Mixed-Integer
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