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2018 | OriginalPaper | Buchkapitel

37. Metaheuristics for Natural Gas Pipeline Networks

verfasst von : Roger Z. Ríos-Mercado

Erschienen in: Handbook of Heuristics

Verlag: Springer International Publishing

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Abstract

In this chapter an overview of metaheuristic algorithms that have been very successful in tackling a particular class of natural gas pipeline network optimization problems is presented. In particular, the problem of minimizing fuel consumption incurred by the compressor stations driving natural gas in pipeline networks is addressed. This problem has been studied from different angles over the past few years by virtue of its tremendous economical impact. First, a general mathematical framework for this class of problems is presented. After establishing the most relevant model properties and fundamental network topologies, which are key factors for choosing an appropriate solution technique, current state-of-the-art metaheuristics are presented for handling different versions of this problem. This work concludes by highlighting the most relevant and important challenges of this very exciting area of research in natural gas transportation networks.

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Vorheriges Kapitel Metaheuristics for Medical Image Registration
Nächstes Kapitel Network Optimization
Literatur
1.
Aalto H (2008) Optimal control of natural gas pipeline networks: a real-time, model-based, receding horizon optimisation approach. VDM Verlag, Saarbrücken
2.
Anglard P, David P (1988) Hierarchical steady state optimization of very large gas pipelines. In: Proceedings of the 20th PSIG annual meeting, Toronto
3.
Borraz-Sánchez C, Haugland D (2011) Minimizing fuel cost in gas transmission networks by dynamic programming and adaptive discretization. Comput Ind Eng 61(2):364–372
4.
Borraz-Sánchez C, Ríos-Mercado RZ (2005) A hybrid meta-heuristic approach for natural gas pipeline network optimization. In: Blesa MJ, Blum C, Roli A, Sampels M (eds) Hybrid metaheuristics. Springer, Berlin, pp 54–65
5.
Borraz-Sánchez C, Ríos-Mercado RZ (2009) Improving the operation of pipeline systems on cyclic structures by tabu search. Comput Chem Eng 33(1):58–64
6.
Carter RG (1998) Pipeline optimization: dynamic programming after 30 years. In: Proceedings of the 30th PSIG annual meeting, Denver
7.
Chebouba A, Yalaoui F, Smati A, Amodeo L, Younsi K, Tairi A (2009) Optimization of natural gas pipeline transportation using ant colony optimization. Comput Oper Res 36(6):1916–1923
8.
Cobos-Zaleta D, Ríos-Mercado RZ (2002) A MINLP model for minimizing fuel consumption on natural gas pipeline networks. In: Proceedings of the XI Latin-Ibero-American conference on operations research, Concepción
9.
De Wolf D, Smeers Y (2000) The gas transmission problem solved by an extension of the simplex algorithm. Manag Sci 46(11):1454–1465
10.
Domschke P, Geißler B, Kolb O, Lang J, Martin A, Morsi A (2011) Combination of nonlinear and linear optimization of transient gas networks. INFORMS J Comput 23(4):605–617
11.
Ehrhardt K, Steinbach MC (2005) Nonlinear optimization in gas networks. In: Bock HG, Kostina E, Phu HX, Rannacher R (eds) Modeling, simulation and optimization of complex processes. Springer, Berlin, pp 139–148
12.
Flores-Villarreal HJ, Ríos-Mercado RZ (2003) Computational experience with a GRG method for minimizing fuel consumption on cyclic natural gas networks. In: Mastorakis NE, Stathopulos IA, Manikopoulos C, Antoniou GE, Mladenov VM, Gonos IF (eds) Computational methods in circuits and systems applications. WSEAS Press, Athens, pp 90–94
13.
Jin L, Wojtanowocz AK (2010) Optimization of large gas pipeline network – a case study in China. J Can Pet Technol 49(4):36–43
14.
Ke SL, Ti HC (2000) Transient analysis of isothermal gas flow in pipeline network. Chem Eng J 76(2):169–177
15.
Lall HS, Percell PB (1990) A dynamic programming based gas pipeline optimizer. In: Bensoussan A, Lions JL (eds) Analysis and optimization of systems. Lecture notes in control and information sciences, vol 144. Springer, Berlin, pp 123–132
16.
Larson RE, Wismer DA (1971) Hierarchical control of transient flow in natural gas pipeline networks. In: Proceedings of the IFAC symposium on distributed parameter systems, Banff,
17.
Luongo CA, Gilmour BJ, Schroeder DW (1989) Optimization in natural gas transmission networks: a tool to improve operational efficiency. Technical report. Stoner Associates, Inc., Houston
18.
Mahlke D, Martin A, Moritz S (2007) A simulated annealing algorithm for transient optimization in gas networks. Math Methods Oper Res 66(1):99–115
19.
Mantri VB, Preston LB, Pringle CS (1985) Transient optimization of a natural gas pipeline system. In: Proceedings of the 17th PSIG annual meeting, Albuquerque
20.
Martin A, Möller M, Moritz S (2006) Mixed integer models for the stationary case of gas network optimization. Math Program 105(2–3):563–582
21.
Osiadacz AJ (1994) Dynamic optimization of high pressure gas networks using hierarchical systems theory. In: Proceedings of the 26th PSIG annual meeting, San Diego
22.
Osiadacz AJ (1998) Hierarchical control of transient flow in natural gas pipeline systems. Int Trans Oper Res 5(4):285–302
23.
Osiadacz AJ, Bell DJ (1986) A simplified algorithm for optimization of large-scale gas networks. Optim Control Appl Methods 7(1):95–104
24.
Osiadacz AJ, Chaczykowski M (2001) Comparison of isothermal and non-isothermal pipeline gas flow models. Chem Eng J 81(1):41–51
25.
Osiadacz AJ, Swierczewski S (1994) Optimal control of gas transportation systems. In: Proceedings of the 3rd IEEE conference on control applications, Glasgow, pp 795–796. ISBN:0-7803-1872-2
26.
Percell PB, Ryan MJ (1987) Steady-state optimization of gas pipeline network operation. In: Proceedings of the 19th PSIG annual meeting, Tulsa
27.
Pratt KF, Wilson JG (1984) Optimisation of the operation of gas transmission systems. Trans Inst Meas Control 6(5):261–269
28.
Ríos-Mercado RZ (2002) Natural gas pipeline optimization. In: Pardalos PM, Resende MGC (eds) Handbook of applied optimization, chap 18.8.3. Oxford University Press, New York, pp 813–825
29.
Ríos-Mercado RZ, Borraz-Sánchez C (2015) Optimization problems in natural gas transportation systems: a state-of-the-art review. Appl Energy 147:536–555
30.
Ríos-Mercado RZ, Wu S, Scott LR, Boyd EA (2002) A reduction technique for natural gas transmission network optimization problems. Ann Oper Res 117(1–4):217–234
31.
Ríos-Mercado RZ, Kim S, Boyd EA (2006) Efficient operation of natural gas transmission systems: a network-based heuristic for cyclic structures. Comput Oper Res 33(8):2323–2351
32.
Schmidt M, Steinbach MC, Willert BM (2015) High detail stationary optimization models for gas networks. Optim Eng 16(1):131–164
33.
Suresh K, Ghosh S, Kundu D, Sen A, Das S, Abraham A (2008) Inertia-adaptive particle swarm optimizer for improved global search. In: Proceedings of the eighth international conference on intelligent systems design and applications. IEEE Computer Society, Los Alamitos, pp 253–258
34.
Tabkhi F, Pibouleau L, Hernandez-Rodriguez G, Azzaro-Pantel C, Domenech S (2010) Improving the performance of natural gas pipeline networks fuel consumption minimization problems. AIChE J 56(4):946–964
35.
Tao WQ, Ti HC (1998) Transient analysis of gas pipeline network. Chem Eng J 69(1):47–52CrossRef
36.
Wong PJ, Larson RE (1968a) Optimization of natural-gas pipeline systems via dynamic programming. IEEE Trans Autom Control AC–13(5):475–481
37.
Wong PJ, Larson RE (1968b) Optimization of tree-structured natural-gas transmission networks. J Math Anal Appl 24(3):613–626MathSciNetCrossRef
38.
Wu S, Ríos-Mercado RZ, Boyd EA, Scott LR (2000) Model relaxations for the fuel cost minimization of steady-state gas pipeline networks. Math Comput Model 31(2–3):197–220CrossRef
39.
Wu X, Li C, Jia W, He Y (2014) Optimal operation of trunk natural gas pipelines via an inertia-adaptive particle swarm optimization algorithm. J Nat Gas Sci Eng 21:10–18CrossRef
40.
Zheng QP, Rebennack S, Iliadis NA, Pardalos PM (2010) Optimization models in the natural gas industry. In: Rebennack S, Pardalos PM, Pereira MVF, Iliadis NA (eds) Handbook of power systems I, energy systems. Springer, Berlin, pp 121–148
Metadaten
Titel
Metaheuristics for Natural Gas Pipeline Networks
verfasst von
Roger Z. Ríos-Mercado
Copyright-Jahr
2018
Buch
Handbook of Heuristics

Print ISBN: 978-3-319-07123-7

Electronic ISBN: 978-3-319-07124-4

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-07124-4_51

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