Techno-economic dataset for hydrogen storage-based microgrids

被引:0
|
作者
Rozzi, Elena [1 ,2 ]
Minuto, Francesco D. [1 ,2 ]
Lanzini, Andrea [1 ,2 ]
机构
[1] Politecn Torino, Dept Energy, Corso Duca Abruzzi 24, I-10129 Turin, Italy
[2] Politecn Torino, Energy Ctr Lab, Via Paolo Borsellino 38, I-10138 Turin, Italy
来源
DATA IN BRIEF | 2024年 / 56卷
关键词
Electrolyser; Fuel cell; Hydrogen storage; Battery energy storage system; capital costs; Operational Costs; Efficiency; Operational Lifetime; POWER-TO-GAS; ENERGY-STORAGE; FUEL-CELL; WATER ELECTROLYSIS; COST; GENERATION;
D O I
10.1016/j.dib.2024.110795
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The challenge of energy storage is a pivotal consideration in renewable energy-based power systems. Hydrogen emerges as a highly promising alternative or complementary solution to electric batteries, showcasing its potential for longterm and high-capacity storage. In this context, energy system modeling and optimization has gained prominence as an indispensable research tool, aiding in the processes of designing, sizing, and managing the day-to-day operations of renewable energy systems integrated with a hydrogen storage unit. However, the gathering of reliable and accurate techno-economic data emerges as time-consuming tasks, and the lack of standardized reference data introduces variability in model results. This variability arises from inconsistent input parameters rather than the physics or complexity of energy systems, leading to potentially erroneous results and misguided policy recommendations. Recognizing the need for comprehensive and transparent datasets, we introduce this open data techno-economic repository. The dataset is meticulously designed to encompass key technologies essential for hydrogen production, compression, storage, and utilization within a power-to-power system. Specifically, technoeconomic data are reported for electrolysers, fuel cells, battery energy storage systems, hydrogen compression units, and hydrogen storage vessels. The learning curves and cost functions embedded in this paper, delineating investment costs as a function of production scale up and size, are de rived directly from the raw data, providing a nuanced under- standing of the economic landscape.
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页数:16
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