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Risk neutral and risk averse approaches to multistage renewable investment planning under uncertainty

机译:不确定性下的风险中性和规避风险的多阶段可再生能源投资计划

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Strategies for investing in renewable energy projects present high risks associated with generation and price volatility and dynamics. Existing approaches for determining optimal strategies are based on real options theory, that often simplify the uncertainty process, or on stochastic programming approaches, that simplify the dynamic aspects. In this paper, we bridge the gap between these approaches by developing a multistage stochastic programming approach that includes real options such as postponing, hedging with fixed (forward) contracts and combination with other sources. The proposed model is solved by a procedure based on the Stochastic Dual Dynamic Programming (SDDP) method. The framework is extended to the risk averse setting. A specific case study in investment in hydro and wind projects in the Brazilian market is used to illustrate that the investment strategies generated by the proposed approach are efficient. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
机译:投资可再生能源项目的战略存在与发电,价格波动和动态相关的高风险。现有的确定最优策略的方法是基于实物期权理论的,它通常可以简化不确定性过程,或者基于随机规划方法,可以简化动态方面。在本文中,我们通过开发一种多阶段随机编程方法来弥合这两种方法之间的差距,该方法包括诸如延期,固定(远期)合约套期以及与其他来源组合之类的实际选择。该模型通过基于随机双动态规划(SDDP)方法的程序求解。该框架扩展到风险规避环境。在巴西市场的水电和风能项目投资中的特定案例研究用于说明所提出的方法所产生的投资策略是有效的。 (C)2015年Elsevier B.V.和国际运营研究学会联合会(IFORS)中的欧洲运营研究学会协会(EURO)。版权所有。

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