Energy and environmental systems planning under uncertainty-An inexact fuzzy-stochastic programming approach

被引:86
|
作者
Li, Y. F. [1 ]
Li, Y. P. [1 ]
Huang, G. H. [1 ]
Chen, X. [2 ]
机构
[1] N China Elect Power Univ, Res Acad Energy & Environm Studies, Beijing 102206, Peoples R China
[2] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, Key Lab Oasis Ecol & Desert Environm, Urumqi 830011, Xinjiang, Peoples R China
关键词
Energy and environmental systems; Energy policy; Fuzzy; Integer programming; Multistage; Optimization; Planning; Uncertainty; SOLID-WASTE MANAGEMENT; WATER-RESOURCES MANAGEMENT; DYNAMIC OPTIMIZATION APPROACH; QUALITY MANAGEMENT; MODEL; CONSTRAINTS; REMEDIATION; OBJECTIVES; SIMULATION; STRATEGIES;
D O I
10.1016/j.apenergy.2010.02.030
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this study, an inexact fuzzy-stochastic energy model (IFS-EM) is developed for planning energy and environmental systems (EES) management under multiple uncertainties. In the IFS-EM, methods of interval parameter fuzzy linear programming (IFLP) and multistage stochastic programming with recourse (MSP) are introduced into a mixed-integer linear programming (MILP) framework, such that the developed model can tackle uncertainties described in terms of interval values, fuzzy sets and probability distributions. Moreover, it can reflect dynamic decisions for facility-capacity expansion and energy supply over a multistage context. The developed model is applied to a case of planning regional-scale energy and environmental systems to demonstrate its applicability, where three cases are considered based on different energy and environmental management policies. The results indicate that reasonable solutions have been generated. They are helpful for supporting: (a) adjustment or justification of allocation patterns of regional energy resources and services, (b) formulation of local policies regarding energy consumption, economic development and environmental protection, and (c) in-depth analysis of tradeoffs among system cost, satisfaction degree and environmental requirement under multiple uncertainties. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3189 / 3211
页数:23
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