| Title |
Large-Scale Energy Infrastructure Optimization: Breakthroughs and Challenges of CO2 Capture and Storage (CCS) Modeling |
| ID_Doc |
77362 |
| Authors |
Eccles, JK; Middleton, RS |
| Title |
Large-Scale Energy Infrastructure Optimization: Breakthroughs and Challenges of CO2 Capture and Storage (CCS) Modeling |
| Year |
2018 |
| Published |
|
| DOI |
10.1007/978-3-642-37896-6_14 |
| Abstract |
Secure, sustainable, and cost-effective energy development will be one of the greatest global challenges in coming decades. This development will include an extensive range of energy resources including coal, conventional and unconventional oil and natural gas, wind, solar, biofuels, geothermal, and nuclear. CO2 capture and storage (CCS) infrastructure is a key example; meaningful CCS in the US could involve capturing CO2 from hundreds of CO2 sources, including coal-fired and natural gas power plants, and transporting a volume of CO2 greater than US oil consumption. Here, we highlight breakthroughs and future challenges for CCS infrastructure optimization and modeling. We start with the evolution of CCS infrastructure modeling from early attempts to represent the capture (sources), transport (network), and storage (sinks) of CO2, through to the integration of more advanced spatial optimization (or location-allocation) approaches including mixed integer-linear programming. We then highlight key future challenges and opportunities, including the representation of significant uncertainties throughout the CCS supply chain and the ability to represent policy and business decisions into CCS infrastructure optimization. Finally, we examine the role that next-generation CCS infrastructure modeling can have in wider massive-scale energy network investments. |
| Author Keywords |
CO2 capture and storage (CCS); Spatial optimization; Uncertainty; Mixed integer-linear programs (MIP) |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Book Citation Index – Social Sciences & Humanities (BKCI-SSH); Book Citation Index – Science (BKCI-S) |
| EID |
WOS:000435581400014 |
| WoS Category |
Computer Science, Information Systems; Computer Science, Interdisciplinary Applications; Geography; Geosciences, Multidisciplinary; Social Sciences, Mathematical Methods |
| Research Area |
Computer Science; Geography; Geology; Mathematical Methods In Social Sciences |
| PDF |
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