Optimization of natural gas transport pipeline network layout: a new methodology based on dominance degree model

At the phase of 13-th five-year plan in China, natural gas will play an important role in energy revolution. With the growth of consumption, natural gas infrastructures will become hot spots of future investment and pipeline network construction will also usher in a period of rapid development. Therefore, it is of great theoretical and practical significance to study layout methods of transport pipeline network. This paper takes natural gas transport pipeline network as a research object, introduces dominance degree to analyse benefits of pipeline projects. Then, this paper proposes Dominance Degree Model (DDM) of transport pipeline projects based on Potential Model (PM) and Economic Potential Theory (EPT). According to DDM of gas transport pipeline projects, layout methods of pipeline network are put forward, which is simple and easy to obtain the overall optimal solution and ensure maximum comprehensive benefits. What’s more, construction sequences of gas transport pipeline projects can be also determined. Finally, the model is applied to a real case of natural gas transport pipeline projects in Zhejiang Province, China. The calculation results suggest that the model should deal with the transport pipeline network layout problem well, which have important implications for other potential pipeline networks not only in the Zhejiang Province but also throughout China and beyond.

[1]  Hai Zhou,et al.  Efficient Steiner tree construction based on spanning graphs , 2003, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[2]  P. Linares,et al.  Energy Efficiency: Economics and Policy , 2010 .

[3]  Witold Pedrycz,et al.  Neural network based decision model, used for design of rural natural gas systems , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[4]  P. K. S. Nain,et al.  Optimization of Natural Gas Pipeline Design and Its Total Cost Using GA , 2012 .

[5]  Dae-Man Han,et al.  Design and implementation of smart home energy management systems based on zigbee , 2010, IEEE Transactions on Consumer Electronics.

[6]  L. Mátyás The Gravity Model: Some Econometric Considerations , 1998 .

[7]  Martin Schmidt,et al.  High detail stationary optimization models for gas networks , 2015 .

[8]  Jamal Shamsie,et al.  THE CONTEXT OF DOMINANCE: AN INDUSTRY-DRIVEN FRAMEWORK FOR EXPLOITING REPUTATION , 2003 .

[9]  Sita Bhaskaran,et al.  Optimal diameter assignment for gas pipeline networks , 1979 .

[10]  Halit Üster,et al.  Optimization for Design and Operation of Natural Gas Transmission Networks , 2014 .

[11]  Stuart E. Dreyfus,et al.  Applied Dynamic Programming , 1965 .

[12]  Javad Mahmoudimehr,et al.  Optimal design of a natural gas transmission network layout , 2013 .

[13]  Ronald L. Graham,et al.  On the History of the Minimum Spanning Tree Problem , 1985, Annals of the History of Computing.

[14]  Shini Peng,et al.  Layout optimization of natural gas network planning: Synchronizing minimum risk loss with total cost , 2016 .

[15]  Yuan Taur,et al.  An analytic potential model for symmetric and asymmetric DG MOSFETs , 2006, IEEE Transactions on Electron Devices.

[16]  M. Sniedovich Dijkstra's algorithm revisited: the dynamic programming connexion , 2006 .

[17]  Andre K. Geim,et al.  Electric Field Effect in Atomically Thin Carbon Films , 2004, Science.

[18]  Thomas F. Edgar,et al.  Optimal Design of Gas Transmission Networks , 1978 .