Stochastic MILP model for optimal timing of investments in CO2 capture technologies under uncertainty in prices

Reduction in greenhouse gas emissions of existing coal-fired power plants is a necessary action to attain the global reductions committed in the Kyoto Protocol. In the framework of a cap and trade system, we propose a two-stage stochastic mixed-integer linear programming (MILP) approach for the opti...

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Veröffentlicht in:Energy (Oxford) Jg. 54; S. 343 - 351
Hauptverfasser: Cristóbal, Jorge, Guillén-Gosálbez, Gonzalo, Kraslawski, Andrzej, Irabien, Angel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.06.2013
Elsevier
Schlagworte:
Applied sciences
carbon dioxide
carbon sequestration
case studies
CO2 capture technology
coal
Coal-based electricity production
Energy
environmental markets
Exact sciences and technology
Financial risk
greenhouse gas emissions
industry
linear programming
MILP model
power plants
prices
risk
Stochastic CO2 prices
Uncertainty
Coal-based electricity production
Uncertainty
CO2 capture technology
MILP model
Financial risk
Stochastic CO2 prices
CO2 sequestration
Models
Price
Modeling
Investment
ISSN:0360-5442
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Zusammenfassung:Reduction in greenhouse gas emissions of existing coal-fired power plants is a necessary action to attain the global reductions committed in the Kyoto Protocol. In the framework of a cap and trade system, we propose a two-stage stochastic mixed-integer linear programming (MILP) approach for the optimal investment timing and operation of a CO2 capture system under uncertainty in the CO2 allowance price. In the MILP, uncertainties are modeled via scenarios that are generated from a set of probability functions obtained using the Geometric Brownian Motion (GBM) approach in conjunction with Monte Carlo sampling. The model takes into account two economic objectives: the expected net profit and the financial risk. We demonstrate the capabilities of the tool presented through a case study based on a coal fired power plant. Our MILP approach can be applied to a wide range of processes and industries that deal with carbon sequestration issues. ► We search the optimal investment timing and operational decisions in CCS technology. ► We propose a two-stage stochastic mixed-integer linear programming problem (MILP). ► Uncertain CO2 prices are introduced via scenarios using GBM and Monte Carlo sampling. ► Solutions selected must maximize the expected profit and minimize the financial risk. ► This decision tool will help to select between risk-taker and risk-averse solutions.
Bibliographie:http://dx.doi.org/10.1016/j.energy.2013.01.068
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ISSN:0360-5442
DOI:10.1016/j.energy.2013.01.068