Risk-Constrained Stochastic Optimization Methods for Dealing with Uncertain Technological Learning in Energy Systems

摘要：

To date, optimization models of uncertain endogenous technological change models commonly add cost resulting from overestimating technological learning rates into an objective function with a subjective risk factor. This paper explores two risk-constrained stochastic optimization methods for dealing with uncertain technological learning with a simplified energy system model. The model assumes one primary resource and the economy demands one homogenous goods. There are three technologies, namely existing, incremental, and revolutionary, can be used to produce the goods from the resource. The existing technology has no learning potential; the incremental technology has a deterministic mild leaning potential; and the revolutionary technology has high but uncertain learning potential.

作者: Tieju Ma Chunjie Chi Jun Chen

作者单位: School of Business, East China University of Science and Technology

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 1549-1553

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）