ICCSIP: An inexact chance-constrained semi-infinite programming approach for energy systems planning under uncertainty

被引:39
作者
Guo, P. [1 ]
Huang, G. H. [2 ]
He, L. [1 ]
Cai, Y. P. [1 ,3 ]
机构
[1] Univ Regina, Fac Engn, Environm Syst Engn Program, Regina, SK S4S 0A2, Canada
[2] Univ Waterloo, Dept Civil & Environm Engn, Waterloo, ON N2L 3G1, Canada
[3] Beijing Normal Univ, Chinese Res Acad Environm Sci, Beijing 100875, Peoples R China
基金
加拿大自然科学与工程研究理事会;
关键词
chance-constrained programming; energy management system; functional interval; semi-infinite programming; uncertainty;
D O I
10.1080/15567030801928961
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
This article developed an inexact chance-constrained semi-infinite programming (ICCSIP) method for the energy management system under functional interval uncertainties. The approach not only considers the left-hand interval parameters, right-hand distribution information, and the probability of violating constraint, but also deals with functional interval uncertainty, which extends the range of the uncertainties. A regional energy management system is applied to illustrate the applicability of the ICCSIP approach. In consideration of energy sources allocation, fuel prices, and environmental regulations, a systematic planning of the regional energy structure is desired to bring a significant increase of economic benefit and improvement of environmental quality. This problem can be formulated as a programming model with an objective of minimizing the overall system costs subject to a number of environmental, economic and energy sources availability constraints. The programming results indicate that reasonable and useful decision alternatives can be generated under different probabilities of violating the system constraints. The obtained results are useful for decision makers to gain an insight into the tradeoffs among environmental, economic and system reliability criteria.
引用
收藏
页码:1345 / 1366
页数:22
相关论文
共 40 条
[1]   Evaluating solvency versus efficiency performance and different forms of organization and marketing in US property - liability insurance companies [J].
Brockett, PL ;
Cooper, WW ;
Golden, LL ;
Rousseau, JJ ;
Wang, YY .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2004, 154 (02) :492-514
[2]   Redefining chance-constrained programming in fuzzy environment [J].
Chakraborty, D .
FUZZY SETS AND SYSTEMS, 2002, 125 (03) :327-333
[3]  
CHANG NB, 1997, J OPER RES, V32, P303
[4]   Optimisation models for decision support in the development of biomass-based industrial district-heating networks in Italy [J].
Chinese, D ;
Meneghetti, A .
APPLIED ENERGY, 2005, 82 (03) :228-254
[5]  
*CIMS, 1999, DEV MAINT EN RES GRO
[6]   Waste management modeling by MARKAL model: A case study for Basilicata Region [J].
Cosmi, C ;
Cuomo, V ;
Macchiato, M ;
Mangiamele, L ;
Masi, S ;
Salvia, M .
ENVIRONMENTAL MODELING & ASSESSMENT, 2000, 5 (01) :19-27
[7]   Linear programming with fuzzy coefficients in constraints [J].
Fang, SC ;
Hu, CF ;
Wang, HF ;
Wu, SY .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 1999, 37 (10) :63-76
[8]   Innovations in energy efficient and environmentally friendly space-conditioning systems [J].
Garimella, S .
ENERGY, 2003, 28 (15) :1593-1614
[9]   Linear semi-infinite programming theory:: An updated survey [J].
Goberna, MA ;
López, MA .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2002, 143 (02) :390-405
[10]   ISMISIP: an inexact stochastic mixed integer linear semi-infinite programming approach for solid waste management and planning under uncertainty [J].
Guo, P. ;
Huang, G. H. ;
He, L. .
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2008, 22 (06) :759-775