Multiscale whole systems modelling and analysis for CO2 capture, transport and storage

二氧化碳捕获、运输和储存的多尺度整体系统建模和分析

• 批准号: NE/H013865/1
• 负责人: Meihong Wang
• 金额: $ 42.33万
• 依托单位: CRANFIELD UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FH013865%2F1
• 关键词: Multiscale; whole; systems; modelling; analysis

The UK has challenging GHG reduction targets. It is believed that carbon capture and storage (CCS) will play a critical role in the energy systems of the future, in part to support the decarbonisation objective and in part to provide grid flexibility in a future system including a large fraction of less responsive low carbon energy systems (e.g. nuclear baseload and intermittent wind). The whole systems modelling and analysis programme proposed here is designed to support wider UK initiatives by reducing technological risk and identifying performance bottlenecks. CCS will require substantial capital investment in capture and transport systems and storage complex management. Although elements of the whole chain have been studied through modelling and experimentation, there is little work on whole system assessment. For complex systems such as CCS, whole system assessment is vital ahead of large scale deployment as it identifies critical integration and interaction issues between the components and evaluates whole system performance as a function of component design parameters. Thus the whole system may be optimised; simply optimising the design of individual components is likely to result in a sub-optimal system design. The proposed research methodology is based on multiscale modelling. This involves the development of fit-for-purpose models of the individual components which describe phenomena that operate over different length and time scales and which support integration and data exchange across scales. The reason for this is that relatively localised phenomena (e.g. mass transfer in an amine scrubber) might affect the overall system transient response by limiting the rate at which the power plant flue gas flowrate can be turned up or down. Similarly, the important performance trade-offs in individual component designs must be characterised and used for overall system design. There are a number of important issues to be resolved regarding future CCS systems; the applicants believe that multiscale systems modelling approach is ideal to develop relevant insights and guidance. Examples of the issues to be addressed through whole systems modelling, analysis and optimisation include: - The development and application of a methodology to optimise the time-phased evolution of the whole CCS system design (incorporating its important individual components), including sources to recruit and location of storage sites, balancing long-term and short-term investment imperatives. - Performing integrated assessments of alternative CCS systems, through the application of fit-for-purpose models (e.g. those able to quantify trace emissions of harmful substances) and rigorous life-cycle based analyses. - Characterising the transient performance of the integrated system (how will it perform in actual operation?), understanding whether or not it affects the flexibility of the wider energy system with which it is interfaced, what the safety critical components are and the network's dynamic stability and operability bottlenecks - Understand issues of systems integration - how do the different phenomena associated with the different components in the system cause effects to propagate through the network (e.g. the effect of impurities in captured CO2, the transport network and the storage complex). What are the important considerations that must be taken into consideration when designing and operating the whole system? The outcome of the programme will be relevant to a very wide range of stakeholders interested in CCS, including industry, regulatory and policy agencies and academia. The most important contributions of the project will be: - making available methodologies to design and analyse future CCS systems - generating insights into the most important interactions involved in system design and operation - quantifying (economics, environmental impact, safety & operability) the performance of UK CCS systems

英国对温室气体减排目标提出了挑战。人们认为，碳捕集与封存（CCS）将在未来的能源系统中发挥关键作用，一方面是为了支持脱碳目标，另一方面是为了在未来的系统中提供电网灵活性，其中包括很大一部分响应性较低的低碳能源系统（例如核基本负荷和间歇性风能）。这里提出的整个系统建模和分析方案旨在通过减少技术风险和识别性能瓶颈来支持更广泛的英国倡议。CCS将需要在捕集和运输系统以及存储复杂管理方面进行大量资本投资。虽然通过建模和实验研究了整个链条的要素，但对整个系统的评估工作很少。对于像CCS这样的复杂系统，在大规模部署之前，整个系统评估是至关重要的，因为它可以识别组件之间的关键集成和交互问题，并评估作为组件设计参数函数的整个系统性能。因此，整个系统可以得到优化；简单地优化单个组件的设计很可能导致次优系统设计。提出的研究方法是基于多尺度建模。这涉及到为各个组件开发适合目的的模型，这些模型描述了在不同长度和时间尺度上运行的现象，并支持跨尺度的集成和数据交换。这样做的原因是，相对局部的现象（例如胺洗涤器中的传质）可能会通过限制电厂烟气流量可以提高或降低的速率来影响整个系统的瞬态响应。同样，单个组件设计中的重要性能权衡必须被描述并用于整个系统设计。关于未来的CCS系统，有许多重要的问题需要解决；申请人认为，多尺度系统建模方法是发展相关见解和指导的理想方法。通过整个系统建模、分析和优化来解决的问题的例子包括：-开发和应用一种方法来优化整个CCS系统设计的分阶段发展（包括其重要的单个组件），包括招募资源和存储地点的位置，平衡长期和短期投资需求。-通过应用适合用途的模型（例如能够量化有害物质痕量排放的模型）和严格的基于生命周期的分析，对备选CCS系统进行综合评估。-描述集成系统的暂态性能（它在实际运行中会如何表现？），了解它是否会影响其所连接的更广泛的能源系统的灵活性；安全关键组件是什么，网络的动态稳定性和可操作性瓶颈-了解系统集成的问题-与系统中不同组件相关的不同现象如何导致影响通过网络传播（例如，捕获的二氧化碳中杂质的影响，运输网络和存储综合体）。在设计和操作整个系统时，必须考虑哪些重要因素？该计划的结果将涉及对CCS感兴趣的广泛利益相关者，包括工业、监管和政策机构以及学术界。该项目最重要的贡献将是：-提供设计和分析未来CCS系统的可用方法-对系统设计和运行中涉及的最重要的相互作用产生见解-量化（经济，环境影响，安全性和可操作性）英国CCS系统的性能

项目成果

Demonstrating full-scale post-combustion CO2 capture for coal-fired power plants through dynamic modelling and simulation

• DOI: 10.1016/j.fuel.2010.10.056
• 发表时间: 2012-11
• 期刊: Fuel
• 影响因子: 7.4
• 作者: A. Lawal;Meihong Wang;P. Stephenson;O. Obi

Process Simulation and Analysis for CO2 Transport Pipeline Design and Operation – Case Study for the Humber Region in the UK

• DOI: 10.1016/b978-0-444-63455-9.50107-0
• 发表时间: 2014
• 期刊: Computer-aided chemical engineering
• 作者: Xiaobo Luo;K. Mistry;C. Okezue;Meihong Wang;R. Cooper;Eni Oko;J. Field

Dynamic modelling and analysis of post-combustion CO2 chemical absorption process for coal-fired power plants

• DOI: 10.1016/j.fuel.2010.05.030
• 发表时间: 2010-10-01
• 期刊: FUEL
• 影响因子: 7.4
• 作者: Lawal, A.;Wang, M.;Yeung, H.
• 通讯作者: Yeung, H.