Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA.
Sci Rep. 2023 Apr 21;13(1):6527. doi: 10.1038/s41598-023-33512-5.
The design of optimal infrastructure is essential for the deployment of commercial and large-scale carbon capture and storage (CCS) technology. During the design process, it is important to consider CO capture and storage locations and CO transportation pipelines to minimize the total project cost. SimCCS, first introduced in 2009, is an integrated open-source tool to optimize CCS infrastructure. The core CCS infrastructure design problem in SimCCS is structured as a mixed-integer linear programming problem by selecting the optimal pipeline routes, searching CO source capture and storage locations, and determining the corresponding CO amounts to meet desired capture targets. Multiple important and practical features have been developed to the latest version of SimCCS, SimCCS. One of these features is phase-based modeling which enables users to dynamically design the CCS infrastructure. We demonstrate the phased-based modeling capability using two CCS infrastructure optimization case studies. The results from these case studies reveal that the phase-based modeling capability in SimCCS is particularly useful to optimize the dynamic deployment of CCS projects.
优化基础设施的设计对于商业和大规模碳捕集与封存(CCS)技术的部署至关重要。在设计过程中,重要的是要考虑 CO 捕集和封存地点以及 CO 运输管道,以最大限度地降低项目总成本。SimCCS 于 2009 年首次推出,是一个用于优化 CCS 基础设施的集成开源工具。SimCCS 中的核心 CCS 基础设施设计问题通过选择最佳管道路线、搜索 CO 源捕集和封存地点以及确定相应的 CO 量来满足预期的捕集目标,被结构化为混合整数线性规划问题。SimCCS 的最新版本 SimCCS 还开发了多个重要的实用功能。其中一个功能是基于阶段的建模,它使用户能够动态设计 CCS 基础设施。我们使用两个 CCS 基础设施优化案例研究展示了基于阶段的建模能力。这些案例研究的结果表明,SimCCS 中的基于阶段的建模能力对于优化 CCS 项目的动态部署特别有用。