Decision rule approximations for the risk averse reservoir management problem

被引:13
作者
Gauvin, Charles [1 ,2 ,3 ]
Delage, Erick [2 ,4 ]
Gendreau, Michel [1 ,3 ]
机构
[1] Polytech Montreal, CP 6079, Montreal, PQ H3C 3A7, Canada
[2] Gerad, 3000 Chemin Cote St Catherine, Montreal, PQ H3T 2A7, Canada
[3] CIRRELT, CP 6128, Montreal, PQ H3C 3J7, Canada
[4] HEC Montreal, 3000 Chemin Cote St Catherine, Montreal, PQ H3T 2A7, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Stochastic programming; Robust optimization; Risk analysis; OR in energy; ROBUST OPTIMIZATION; STOCHASTIC OPTIMIZATION; DECOMPOSITION; AGGREGATION; OPERATION;
D O I
10.1016/j.ejor.2017.01.044
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper presents a new formulation for the risk averse stochastic reservoir management,problem. Using recent advances in robust optimization and stochastic programming, we propose a multi-stage model based on minimization of a risk measure associated with floods and droughts for a hydro-electrical complex. We present our model and then identify approximate solutions using standard affine decision rules commonly found in the literature as well as lifted decision rules. Finally, we conduct thorough numerical experiments based on a real river system in Western Quebec and conclude on the relative performance of families of decision rules. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:317 / 336
页数:20
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