The influence of uncertainty in the development of a CO2 infrastructure network

This study aimed to analyze whether, and how, uncertainty influences the layout and costs of a CO2 transportation network. The case without uncertainty is modelled with a perfect foresight (PF) model and with uncertainty with the real option approach (ROA). In this study, uncertainties in the CO2 price, tariff received per tonne of CO2 transported, the willingness, probability and moment-that sources join the CO2 transportation network are incorporated in the analysis. The results show that uncertainty leads to higher required CO2 prices before investments in carbon dioxide capture and storage (CCS) are made. With a volatility of 47% in the CO2 price, the required CO2 price almost triples in comparison with the net present value approach. Hence, under uncertainty less sources are retrofitted with CCS and less CO2 is captured and stored over time. For instance, for the analyzed case study 31 Mt and 137 Mt CO2 is projected to be captured in the base scenario of ROA and PF model, respectively, in the period 2015-2050. If the volatility of the CO2 price is reduced with 50%, 96 Mt is projected to be captured in the ROA, which is still about one third less than in the PF model. Furthermore, the results show that uncertainty leads to less development of trunklines. All this leads to an increase in the transport and storage costs. For instance, for our case study, the average CO2 transport and storage costs in 2050 increase from 2.8 (sic)/t to 13 (sic)/t in the base scenario of the ROA compared to the PF model. If the volatility is reduced with 50%, the transport and storage costs decrease to 7.5 (sic)/t in the ROA, which is still 2.5 times as much as in the PF model. Our findings indicate that the implementation of CCS can best be stimulated by reducing the volatility of the CO2 price, reducing capture costs and facilitating cooperation between nearby sources. (C) 2015 Elsevier Ltd. All rights reserved.