A method for the multi-objective optimization of the operation of natural gas pipeline networks considering supply reliability and operation efficiency

被引:39
|
作者
Su, Huai [1 ]
Zio, Enrico [2 ,3 ]
Zhang, Jinjun [1 ]
Li, Xueyi [1 ]
Chi, Lixun [1 ]
Fan, Lin [1 ]
Zhang, Zongjie [1 ,4 ]
机构
[1] China Univ Petr, Natl Engn Lab Pipeline Safety, MOE Key Lab Petr Engn, Beijing Key Lab Urban Oil & Gas Distribut Technol, Beijing 102249, Peoples R China
[2] Politecn Milan, Dipartimento Energia, Via La Masa 34, I-20156 Milan, Italy
[3] PSL Res Univ, Mines ParisTech, CRC, Sophia Antipolis, France
[4] Petrochina West East Gas Pipeline, Dongfushan Rd 458, Shanghai 200122, Peoples R China
基金
中国国家自然科学基金;
关键词
Natural gas pipeline network; Multi-objective optimization; Supply reliability; Power demand; NSGA-II algorithm; ROBUST OPTIMIZATION; MILP MODEL; FRAMEWORK; SYSTEMS; DESIGN; VULNERABILITY; UNCERTAINTY; MANAGEMENT; SECURITY; CHAIN;
D O I
10.1016/j.compchemeng.2019.106584
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Reliable gas supply for minimum risk of supply shortage and minimum power demand for low energy cost are two fundamental objectives of natural gas pipeline networks. In this paper, a multi-objective optimization method is developed to trade-off reliability and power demand in the decision process. In the optimization, the steady state behavior of the natural gas pipeline networks is considered, but the uncertainties of the supply conditions and customer consumptions are accounted for. The multi-objective optimization regards finding operational strategies that minimize power demand and risk of gas supply shortage. To quantify the probability of supply interruption in pipeline networks, a novel limit function is introduced based on the mass conservation equation. Then, the risk of interruption is calculated by combining the probability of interruption and its consequences, measured in utility terms. The multiobjective optimization problem is solved by the NSGA-II algorithm and its effectiveness is tested on two typical pipeline networks, i.e., a tree-topology network and a loop-topology network. The results show that the developed optimization model is able to find solutions which effectively compromise the need of minimizing gas supply shortage risk and reducing power demand. Finally, a sensitivity analysis is conducted to analyze the impact of demand uncertainties on the optimization results. (C) 2019 Elsevier Ltd. All rights reserved.
引用
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页数:10
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