Affiliation:
1. Los Alamos National Laboratory
Abstract
Abstract
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 CO2 capture and storage locations and CO2 transport 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 is structured as a mixed-integer linear programming problem in SimCCS by selecting the optimal pipeline routes, searching CO2 source capture and storage locations, and determining the corresponding amounts to meet desired capture targets. Multiple important and practical features have been added to the latest version of SimCCS (SimCCS3.0), including (1) the temporal model which enables the user to investigate the impact of the enhanced 45Q tax credits on CCS infrastructure and to implement dynamic evolution of CO2 point sources (decommissioning and shutting down existing facilities and opening of new facilities), and (2) the consideration of utilizing the existing CO2 pipelines. We demonstrate the newly developed features in SimCCS3.0 using one CCS infrastructure optimization case study. The results from these case studies reveal that the inclusion of those developed features is particularly useful to optimize the dynamic deployment of CCS projects. SimCCS3.0 is available for public use via GitHub.
Cited by
1 articles.
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