Modeling a Carbon Capture, Transport, and Storage Infrastructure for Europe

Oei, Pao-Yu; Herold, Johannes; Mendelevitch, Roman

doi:10.1007/s10666-014-9409-3

Cited by 28 publications

(17 citation statements)

References 11 publications

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“…The first investments into the CCTS technology can be seen in the previous years (2020)(2021)(2022)(2023)(2024)(2025). The iron and steel sector is -similar to previous modeling runs in Oei et al (2014) -again the first mover until some cement works start capturing CO 2 from 2035 onwards (see Figure 3). At that point a certificate price of 75 €/tCO 2 is reached and a total of 300 MtCO 2 is annually stored in offshore hydrocarbon fields and saline aquifers.…”

Section: Eu_80% Scenariosupporting

confidence: 67%

“…For our numerical analysis we use the "CCTS-Mod" (Oei et al, 2014). The model is a multiperiod, scalable, mixed integer model coded in GAMS (General Algebraic Modeling Software) and solved with a CPLEX solver.…”

Section: The Model Ccts-modmentioning

confidence: 99%

“…The simplified decision path of the CCTS-Mod is illustrated in Figure 1. A more detailed model description (though without the option of CO 2 -EOR) can be found in Oei et al (2014). The model is well-based in the literature on CCTS infrastructure models, building on models developed by Middleton and Bielicki (2009) and Morbee et al (2012).…”

Section: The Model Ccts-modmentioning

confidence: 99%

“…4 A detailed description of the cost data can be found in Mendelevitch (2014). emission volumes of refineries, steel and cement production facilities as well as coal-and gas-fired power plants is taken from a database developed earlier in Oei, Herold, & Mendelevitch (2014 Source: Own illustration based on Oei, Herold, & Mendelevitch (2014) and Mendelevitch (2014). …”

Section: Datamentioning

confidence: 99%

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European Scenarios of CO2 Infrastructure Investment until 2050

Oei¹,

Mendelevitch²

2016

The Energy Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Scenarios assuming low CO 2 certificate prices lead to hardly any CCTS development in Europe. The iron and steel sector starts deployment as soon as the CO 2 certificate price exceeds 50 €/tCO 2 . The cement sector starts investing at a threshold of 75 €/tCO 2 , followed by the electricity sector when prices exceed 100 €/tCO 2 . Results on the degree of deployment of CCTS are found to be more sensitive to variable cost of CO 2 capture than to investment costs. Additional revenues from using the CO 2 for enhanced oil recovery (CO 2 -EOR) in the North Sea would lead to an earlier adoption of CCTS, independent of the CO 2 certificate price; this case may become especially relevant for the UK, Norway and the Netherlands. On the downside, scattered CCTS deployment increases unit cost of transport and storage infrastructure by 30% and more. Terms of use: Documents in

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Section: Eu_80% Scenariosupporting

confidence: 67%

Section: The Model Ccts-modmentioning

confidence: 99%

Section: The Model Ccts-modmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

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European Scenarios of CO2 Infrastructure Investment until 2050

Oei¹,

Mendelevitch²

2016

The Energy Journal

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“…A series of studies analyzed the technical potential of CCTS deployment, including possible CO 2 pipeline routing (Oei, Herold, and Mendelevitch 2014;Morbee, Serpa, and Tzimas 2012;Middleton and Bielicki 2009;Kazmierczak et al 2008;Kobos et al 2007). The construction of such large-scale new infrastructure networks is highly influenced by public acceptance, especially in densely populated regions such as the European Union (Gough, O‫׳‬Keefe, and Mander 2014).…”

Section: Introductionmentioning

confidence: 99%

The Impact of Policy Measures on Future Power Generation Portfolio and Infrastructure: A Combined Electricity and CCTS Investment and Dispatch Model (ELCO)

Mendelevitch¹,

Oei

2015

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This paper presents a general electricity-CO 2 (ELCO) modeling framework that is able to simulate interactions of the energy-only market with different forms for national policy measures. We set up a two sector model where players can invest into various types of generation technologies including renewables, nuclear and Carbon Capture, Transport, and Storage (CCTS). For a detailed representation of CCTS we also include industry players (iron and steel as well as cement), and CO 2 transport and CO 2 storage including the option for CO 2 enhanced oil recovery (CO 2 -EOR). The players maximize their expected profits based on variable, fixed and investment costs as well as the price of electricity, CO 2 abatement cost and other incentives, subject to technical and environmental constraints. Demand is inelastic and represented via a selection of type hours. The model framework allows for regional disaggregation and features simplified electricity and CO 2 pipeline networks. The model is balanced via a market clearing for the electricity as well as CO 2 market. The equilibrium solution is subject to constraints on CO 2 emissions and renewable generation share. We apply the model to a case study of the UK Electricity Market Reform to illustrate the mechanisms and potential results attained from the model. Terms of use: Documents in

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