An inexact robust nonlinear optimization method for energy systems planning under uncertainty

被引：24

作者：

Chen, C. ^{[1
]}

Li, Y. P. ^{[1
]}

Huang, G. H. ^{[1
]}

Zhu, Y. ^{[1
]}

机构：

[1] N China Elect Power Univ, MOE Key Lab Reg Energy Syst Optimizat, Sinocanada Energy & Environm Res Acad, Beijing 102206, Peoples R China

来源：

RENEWABLE ENERGY | 2012年 / 47卷

关键词：

Robust optimization; Energy systems; Stochastic; Uncertainty; CO2; trading; STOCHASTIC-PROGRAMMING-MODEL; WATER-RESOURCES MANAGEMENT;

D O I：

10.1016/j.renene.2012.04.007

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

In this study, an interval-robust nonlinear optimization (IRNO) method is developed for planning energy system and managing CO2 emissions with trading scheme, through incorporating interval-parameter programming (IPP) within a robust optimization (RO) framework. In the modeling formulation, two recourse actions were adopted to make the model robustness. One of recourse actions was launched to capture the notion of risk in stochastic programming. The other recourse action was seized the risk of shortage electricity amount during the energy system programming process, which successfully emphasizing the safety of energy system under high-variability. The IRNO method is applied to a case of planning energy system with considering the CO2 emissions management. A number of solutions under different robustness levels have been generated. The results obtained can help generate desired decision alternatives that will be able to enhance energy supply safety with a low system-failure risk level and particularly useful for risk-aversive decision makers in handling high-variability conditions. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：55 / 66

页数：12

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