文献类型：期刊文献

英文题名：Risk-constrained stochastic optimization methods for dealing with uncertain technological learning in energy systems

作者：Ma, Tieju[1]; Chi, Chunjie[1]; Chen, Jun[1]

机构：[1] School of Business, East China University of Science and Technology, China

年份：2009

卷号：2

起止页码：499

外文期刊名：Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009

收录：EI(收录号：20094712474245)

语种：英文

外文关键词：Stochastic models - Engineering education

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. ? 2009 IEEE.