A large number of research works were undertaken for the planning of sustainable electricity generation and CO2 mitigation (EGCM) infrastructure design under uncertainty. The typical methodologies assessed the performance of the problem under the variability of the uncertain parameters by optimizing the expected value of the objective function. This approach can have large probabilities of the value optimized in unfavorable scenarios. In this paper, we present a mathematical programming model in planning sustainable electricity generation and CO2 mitigation (EGCM) infrastructure design, including financial risk management under uncertainty. The proposed model allows us to determine available technologies to produce electricity and treat CO2 on the purpose of maximizing the expected total profit and minimizing the financial risk of handling uncertain environments (i.e. CO2 mitigation operating costs, carbon credit prices and electricity prices, etc.), while fulfilling electricity demands and CO2 mitigation standards. The multi-objective optimization problem was solved by using the weighted-sum method that imposes a penalty for risk to the objective function. The capability of the proposed modeling framework is illustrated and applied to a real case study based on Korea, for which valuable insights are obtained. (C) 2012 Elsevier Ltd. All rights reserved.