Cost optimization of offshore wind farm combination with reversible solid oxide cell system producing hydrogen using the PyPSA power system modelling tool
Cost optimization of offshore wind farm combination with reversible solid oxide cell system producing hydrogen using the PyPSA power system modelling tool
复制标题
使用 PyPSA 电力系统建模工具优化海上风电场与可逆固体氧化物电池系统生产氢气的成本优化
DOI：
10.1049/icp.2023.1558
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Guichard J
中科院分区：
文献类型：
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作者：
Guichard J
在实现净零碳目标的背景下，英国制定了一个雄心勃勃的目标，即到2030年拥有5吉瓦的绿色制氢能力。作为EPSRC资助的高效可逆固体氧化物电池（rSOC）项目的一部分，用于使用氢气整合海上可再生能源（ORE），确定了氢气与海上可再生能源相结合的八种情景。使用PyPSA电力系统建模工具结合敏感性研究的模型，在基础设施成本，rSOC系统效率和电价的各种组合下，研究了优化的rSOC系统容量，储氢容量和海底电缆连接容量。初步结果为600兆瓦的风力发电场位于60公里，从海岸结合海上制氢说明电力价格的影响，能源调度决策和优化的基础设施的ORE-rSOC系统。结果表明，高电价波动需要大量的氢气生产和储存能力。输入数据的进一步细化将使这种方法成为用于ORE-rSOC系统设计的有前途的决策工具。
In the context of reaching the net zero carbon target, the UK has set an ambitious target of having a green hydrogen production capacity of 5 GW by 2030. As part of the EPSRC-funded project on high efficiency reversible solid oxide cells (rSOC) for the integration of offshore renewable energy (ORE) using hydrogen, eight scenarios where hydrogen is combined with offshore renewable energy were identified. A model using the PyPSA power system modelling tool combined with a sensitivity study, investigated optimized rSOC system capacities, hydrogen storage capacities, and subsea cable connection capacities under various combinations of infrastructure cost, rSOC system efficiencies, and electricity prices for one of the scenarios. Preliminary results for a 600 MW wind farm situated 60 km from shore combined with offshore hydrogen production illustrate the impact of electricity price on decision-making in energy dispatch and on optimization of infrastructure of an ORE-rSOC system. Results indicate that high electricity price fluctuations call for large amounts of hydrogen production and storage capacity. Further refinement of input data would make this approach a promising decision-making tool for the use in the design of an ORE-rSOC system.