Abstract We present a risk-averse two-stage stochastic programming model for the planning of a hybrid energy system with conventional hydropower component. Using Conditional Value-at-Risk as our measure of risk-aversion, we take into consideration the dispersion of the random total cost arising due to uncertain streamflow amount. We propose an exact solution approach based on scenario decomposition to solve our large scale problem. We then present a case study for the Mediterranean Region in Turkey and generate scenarios using a modified k -nearest neighbor algorithm for bootstrapping the historical time series data of Manavgat River. The results of our computational study show how an optimal solution differs based on the degree of risk-aversion and demonstrate the computational power of our solution approach. Our algorithm is able to solve instances that cannot be solved by CPLEX, furthermore, CPLEX requires 5.84 times more computation time than our algorithm.

中文翻译：

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传统水电混合能源系统规划的风险规避方法

摘要 我们提出了一种规避风险的两阶段随机规划模型，用于规划具有常规水电组件的混合能源系统。使用条件风险价值作为我们的风险规避量度，我们考虑了由于不确定流量而产生的随机总成本的分散。我们提出了一种基于场景分解的精确解决方案来解决我们的大规模问题。然后，我们介绍了土耳其地中海地区的案例研究，并使用改进的 k 最近邻算法生成场景，以引导马纳夫加特河的历史时间序列数据。我们的计算研究结果显示了最佳解决方案如何根据风险规避程度而不同，并证明了我们的解决方案方法的计算能力。