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

Jorge Cristóbal, Gonzalo Guillén-Gosálbez, Andrzej Kraslawski and Angel Irabien

Energy, 2013, vol. 54, issue C, 343-351

Abstract: 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.

Keywords: Coal-based electricity production; CO2 capture technology; Stochastic CO2 prices; Uncertainty; MILP model; Financial risk (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:54:y:2013:i:c:p:343-351

DOI: 10.1016/j.energy.2013.01.068

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