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Operational stability and energy management of a hydrogen-integrated island microgrid considering demand response and renewable curtailment
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DOI：10.1063/5.0321743.png)
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Abstract
En 中文
This study presents the techno-economic, environmental, and advanced operational assessment of a fully renewable, hydrogen-enabled hybrid microgrid designed for the reliable electrification of an off-grid island community. The proposed system integrates solar photovoltaic, wind turbine, biogas generator, fuel cell, electrolyzer, hydrogen storage tank, and battery energy storage system to ensure long-term energy autonomy under variable renewable conditions. Optimal sizing and dispatch results demonstrate a competitive cost of energy of $0.0794/kWh with a net present cost of $333 733, supported by a capital investment of $197 608 and an annual operating cost of $9849. The system achieves net negative carbon emissions of -42.7 kg/yr, highlighting its strong environmental performance, while the levelized cost of hydrogen is estimated at $6.77/kg, indicating the economic feasibility of green hydrogen integration. Beyond conventional techno-economic evaluation, advanced analyses are conducted to validate system robustness. Dynamic voltage and frequency response assessments confirm stable operation under renewable intermittency and load fluctuations. A demand response strategy yields annual energy savings of 19 802.40 kWh, enhancing operational efficiency. Curtailment analysis reveals that hydrogen integration reduces surplus renewable energy by 1 971 487.15 kWh, significantly improving renewable utilization. Furthermore, sensitivity analysis considering solar radiation, wind speed, biomass availability, ambient temperature, nominal discount rate, and inflation rate identifies key parameters influencing system cost and performance. The results collectively demonstrate that hydrogen-assisted hybrid microgrids can deliver cost-effective, stable, and low-carbon energy solutions for remote island electrification.
Keywords:
TECHNOECONOMIC ANALYSIS
SYSTEM
OPTIMIZATION
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