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 50 条
  • [21] Optimization of regional waste management systems based on inexact semi-infinite programming
    He, L.
    Huang, G. H.
    CANADIAN JOURNAL OF CIVIL ENGINEERING, 2008, 35 (09) : 987 - 998
  • [22] Energy and environmental systems planning under uncertainty-An inexact fuzzy-stochastic programming approach
    Li, Y. F.
    Li, Y. P.
    Huang, G. H.
    Chen, X.
    APPLIED ENERGY, 2010, 87 (10) : 3189 - 3211
  • [23] Two-stage chance-constrained programming for system optimization under uncertainty
    Yang, Yu
    18TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE, SYSCON 2024, 2024,
  • [24] A Fuzzy Random Chance-Constrained Programming for Water Distribution System under Uncertainty
    Bao, Peitong
    Wang, Yumin
    JOURNAL OF PIPELINE SYSTEMS ENGINEERING AND PRACTICE, 2024, 15 (04)
  • [25] An Inexact Credibility Chance-Constrained Integer Programming for Greenhouse Gas Mitigation Management in Regional Electric Power System under Uncertainty
    Li, W.
    Bao, Z.
    Huang, G. H.
    Xie, Y. L.
    JOURNAL OF ENVIRONMENTAL INFORMATICS, 2018, 31 (02) : 111 - 122
  • [26] Inexact Fuzzy Chance-Constrained Nonlinear Programming Approach for Crop Water Allocation under Precipitation Variation and Sustainable Development
    Guo, Ping
    Wang, Xiaoling
    Zhu, Hua
    Li, Mo
    JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 2014, 140 (09)
  • [27] A Chance-Constrained Programming based Approach to Optimal Hydro Energy Allocation
    Liu, Guozhong
    Wen, Fushuan
    2008 IEEE 2ND INTERNATIONAL POWER AND ENERGY CONFERENCE: PECON, VOLS 1-3, 2008, : 1233 - 1238
  • [28] Optimal blending under general uncertainties: A chance-constrained programming approach
    Yang, Yu
    COMPUTERS & CHEMICAL ENGINEERING, 2023, 171
  • [29] Advances and applications of chance-constrained approaches to systems optimisation under uncertainty
    Geletu, Abebe
    Kloeppel, Michael
    Zhang, Hui
    Li, Pu
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2013, 44 (07) : 1209 - 1232
  • [30] A chance-constrained programming approach to optimal planning of low-carbon transition of a regional energy system
    Zhang, Jiaqi
    Tian, Guang
    Chen, Xiangyu
    Liu, Pei
    Li, Zheng
    ENERGY, 2023, 278