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Optimizing Renewable Microgrid Performance Through Hydrogen Storage Integration

Gorde:
Argitaratua izan da:Algorithms vol. 18, no. 10 (2025), p. 656-675
Egile nagusia: Ribeiro, Bruno
Beste egile batzuk: Baptista José, Cerveira Adelaide
Argitaratua:
MDPI AG
Gaiak:
Portugal
Fuel cells
Hydrogen storage
Linear programming
Green hydrogen
Hydrogen production
Distributed generation
Energy flow
Integer programming
Emissions
Optimization
Clean energy
Air pollution
Storage capacity
Heat
Electric power grids
Outdoor air quality
Carbon
Efficiency
Electricity consumption
Mathematical programming
Electrolytes
Electricity
Electrolysis
Renewable resources
Carbon dioxide
Energy management
Consumption
Electricity pricing
Energy management systems
Materials durability
Mixed integer
Alternative energy sources
Cost control
Systems stability
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Laburpena:The global transition to a low-carbon energy system requires innovative solutions that integrate renewable energy production with storage and utilization technologies. The growth in energy demand, combined with the intermittency of these sources, highlights the need for advanced management models capable of ensuring system stability and efficiency. This paper presents the development of an optimized energy management system integrating renewable sources, with a focus on green hydrogen production via electrolysis, storage, and use through a fuel cell. The system aims to promote energy autonomy and support the transition to a low-carbon economy by reducing dependence on the conventional electricity grid. The proposed model enables flexible hourly energy flow optimization, considering solar availability, local consumption, hydrogen storage capacity, and grid interactions. Formulated as a Mixed-Integer Linear Programming (MILP) model, it supports strategic decision-making regarding hydrogen production, storage, and utilization, as well as energy trading with the grid. Simulations using production and consumption profiles assessed the effects of hydrogen storage capacity and electricity price variations. Results confirm the effectiveness of the model in optimizing system performance under different operational scenarios.
ISSN:1999-4893
DOI:10.3390/a18100656
Baliabidea:Engineering Database