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Mathematical Methods for the Multi-Criteria Optimization of Structure and Management of Energy Efficient Gas Supply Chains

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Abstract

While the problem of the optimal operation of gas networks has been the object of a large amount of research work, the inclusion of market mechanisms and environmental issues, leading to more complex models resulting in stochastic multiobjective optimization algorithms, has not been considered in its generality. The goal of this article is double: to identify the most general models and algorithms, capable of providing a complete decision support tool, and to show how simplified models can be obtained from them if the complexity of the network makes it necessary to reduce the computational burden.

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References

  1. Van Dam, J., Planning of optimum production from a natural gas field, J. Inst. Pet., 1968, vol. 54, pp. 55–67.

    Google Scholar 

  2. Furey, B.P., A sequential quadratic programmingbased algorithm for optimization of gas networks, Automatica, 1993, vol. 29, pp. 1439–1450.

    Article  Google Scholar 

  3. De Wolf, D. and Smeers, Y., Optimal dimensioning of pipe networks with application to gas transmission networks, Oper. Res., 1996, vol. 44, pp. 596–608.

    Article  Google Scholar 

  4. De Wolf, D. and Smeers, Y., The gas transmission problem solved by an extension of the simplex algorithm, Manage. Sci., 2000, pp. 1454–1465.

    Google Scholar 

  5. Van den Heever, S.A., Grossmann, I.E., Vasantharajan, S., and Edwards, K., A Lagrangean decomposition heuristic for the design and planning of offshore hydrocarbon field infrastructures, Ind. Eng. Chem. Res., 2001, vol. 40, pp. 2857–2875.

    Article  Google Scholar 

  6. Ortíz-Gómez, A., Rico-Ramirez, V., and Hernández-Castro, S., Mixed-integer multiperiod model for the planning of oilfield production, Comput. Chem. Eng., 2002, vol. 26, pp. 703–714.

    Article  Google Scholar 

  7. Möller, M., Mixed integer models for the optimisation of gas networks in the stationary case, PhD Thesis, TU Darmstadt, 2004. http://tuprints.ulb.tu-darmstadt. de/438. Accessed February 22, 2017.

    Google Scholar 

  8. Martin, A., Möller, M., and Moritz, S., Mixed integer models for the stationary case of gas network optimization, Math. Program., 2006, vol. 105, pp. 563–582.

    Article  Google Scholar 

  9. Nimmanonda, P., Uraikul, V., Chan, C.W., and Tontiwachwuthikul, P., Computer-aided simulation model for natural gas pipeline network system operations, Ind. Eng. Chem. Res., 2004, vol. 43, pp. 990–1002.

    Article  CAS  Google Scholar 

  10. Barragán-Hernández, V., Vázquez-Román, R., Rosales-Marines, L., and García-Sánchez, F., A strategy for simulation and optimization of gas and oil production, Comput. Chem. Eng., 2005, vol. 30, pp. 215–227.

    Article  Google Scholar 

  11. Goel, V., Grossmann, I.E., El-Bakry, A.S., and Mulkay, E.L., A novel branch and bound algorithm for optimal development of gas fields under uncertainty in reserves, Comput. Chem. Eng., 2006, vol. 30, pp. 1076–1092.

    Article  CAS  Google Scholar 

  12. Kabirian, A. and Reza Hemmati, M., A strategic planning model for natural gas transmission networks, Energy Policy, 2007, vol. 35, pp. 5656–5670.

    Article  Google Scholar 

  13. Wu, Y., Lai, K.K., and Liu, Y., Deterministic global optimization approach to steady-state distribution gas pipeline networks, Optim. Eng., 2007, vol. 8, pp. 259–275.

    Article  Google Scholar 

  14. Floudas, C.A., Aggarwal, A., and Ciric, A.R., Global optimum search for nonconvex NLP and MINLP problems, Comput. Chem. Eng., 1989, vol. 13, pp. 1117–1132.

    Article  CAS  Google Scholar 

  15. Osiadacz, A.J., Steady state optimisation of gas networks, Arch. Min. Sci., 2011, vol. 56, pp. 335–352.

    Google Scholar 

  16. Osiadacz, A.J. and Chaczykowski, M., Dynamic control for gas pipeline systems, Arch. Min. Sci., 2016, vol. 61, pp. 69–82.

    Google Scholar 

  17. Jonsbråten, T.W., Oil field optimization under price uncertainty, J. Oper. Res. Soc., 1998, vol. 49, pp. 811–818.

    Article  Google Scholar 

  18. Chermak, J.M., Crafton, J., Norquist, S.M., and Patrick, R.H., A hybrid economic-engineering model for natural gas production, Energy Econ., 1999, vol. 21, pp. 67–94.

    Article  Google Scholar 

  19. Wu, S., Ríos-Mercado, R.Z.E., Boyd, A., and Scott, L.R., Model relaxations for the fuel cost minimization of steady-state gas pipeline networks, Math. Comput. Model., 2000, vol. 31, pp. 197–220.

    Article  Google Scholar 

  20. Pindyck, R.S., The dynamics of commodity spot and futures markets: A primer, Energy J., 2001, vol. 22, pp. 1–29.

    Article  Google Scholar 

  21. Cremer, H., Gasmi, F., and Laffont, J.J., Access to pipelines in competitive gas markets, J. Regul. Econ., 2003, vol. 24, pp. 5–33.

    Article  Google Scholar 

  22. Papadakis, I.S. and Kleindorfer, P.R., Optimizing infrastructure network maintenance when benefits are interdependent, OR Spectrum, 2005, vol. 27, pp. 63–84.

    Article  Google Scholar 

  23. Contesse, L., Ferrer, J.C., and Maturana, S., A mixedinteger programming model for gas purchase and transportation, Ann. Oper. Res., 2005, vol. 139, pp. 39–63.

    Article  Google Scholar 

  24. Chen, Z. and Forsyth P.A., A semi-Lagrangian approach for natural gas storage valuation and optimal operation, SIAM J. Sci. Comput., 2007, vol. 30, pp. 339–368.

    Article  Google Scholar 

  25. Chen, H. and Baldick, R., Optimizing short-term natural gas supply portfolio for electric utility companies, IEEE Trans. Power Syst., 2007, vol. 22, pp. 232–239.

    Article  Google Scholar 

  26. Davidson, R.A., Lembo, A.J., Ma, J., Nozick, L.K., and O’Rourke, T.D., Optimization of investments in natural gas distribution networks, J. Energy Eng., 2006, vol. 132, pp. 52–60.

    Article  Google Scholar 

  27. Midthun, K.T., Optimization models for liberalized natural gas markets, PhD Thesis, Norwegian University of Science and Technology, 2007.

    Google Scholar 

  28. Tomasgard, A., Rømo, F., Fodstad, M., and Midthun, K.T., Optimization Models for the Natural Gas Value Chain: Technical Report, Norwegian University of Science, 2007.

    Book  Google Scholar 

  29. Sen, S., Algorithms for stochastic mixed-integer programming models, Handbooks in OR & MS, Aardal, K., Ed., Amsterdam: Elsevier, 2005, vol.12.

  30. Hugo, A. and Pistikopoulos, E., Environmentally conscious long-range planning and design of supply chain networks, J. Cleaner Prod., 2005, vol. 13, pp. 1471–1491.

    Article  Google Scholar 

  31. Srivastava, S., Green supply-chain management: A state-of-the-art literature review, Int. J. Manage. Rev., 2007, vol. 9, pp. 53–80.

    Article  Google Scholar 

  32. Guillén-Gosálbez, G., and Grossmann, I., Optimal design and planning of sustainable chemical supply chains under uncertainty, AIChE J., 2009, vol. 55, pp. 99–121.

    Article  Google Scholar 

  33. Guillén-Gosálbez, G. and Grossmann, I., A global optimization strategy for the environmentally conscious design of chemical supply chains under uncertainty in the damage assessment model, Comput. Chem. Eng., 2009, vol. 34, pp. 42–58.

    Article  Google Scholar 

  34. Ruiz-Femenia, R., Guillén-Gosálbez, G., Jiménez, L., and Caballero, J., Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty, Chem. Eng. Sci., 2013, vol. 95, pp. 1–11.

    Article  CAS  Google Scholar 

  35. Bojarski, A., Laínez, J., Espuña, A., and Puigjaner, L., Incorporating environmental impacts and regulations in a holistic supply chains modeling: An LCA approach, Comput. Chem. Eng., 2009, vol. 33, pp. 1747–1759.

    Article  CAS  Google Scholar 

  36. Bekkering, J., Broekhuis, A.A., and van Gernert, W.J.T., Optimisation of a green gas supply chain—A review, Bioresour. Technol., 2010, vol. 101, pp. 450–456.

    Article  CAS  Google Scholar 

  37. Zhakadiakin, G.V., Medvedeva, A.S., Menshikov, V.V., and Meshalkin, V.P., Supply chain modeling as a tool for balancing environmental performance and profitability in oil and gas industry, in Proc. 19th International Congress of Chemical and Process Engineering, CHISA 2010 and 7th European Congress of Chemical Engineering, ECCE-7, 2010.

    Google Scholar 

  38. Elhedhli, S. and Merrick, R., Green supply chain network design to reduce carbon emissions, Transp. Res. D, 2012, vol. 17, pp. 370–379.

    Article  Google Scholar 

  39. Brandenburg, M., Govindan, K., Sarkis, J., and Seuring, S., Quantitative models for sustainable supply chain management: Developments and directions, Eur. J. Oper. Res., 2014, vol. 233, pp. 299–312.

    Article  Google Scholar 

  40. Balcombe, P., Anderson, K., Speirs, J., Brandon, N., and Hawkes, A., Methane and CO2 emissions from the natural gas supply chain: An evidence assessment, Sustainable Gas Institute, White Paper 1, 2015. http://www.sustainablegasinstitute.org/wp-content/uploads/2015/09/SGI_White_Paper_methaneand-CO2-emissions_WEB-FINAL.pdf?noredirect=1. Accessed February 22, 2017.

    Google Scholar 

  41. Guillén-Gosálbez, G., A novel MILP-based objective reduction method for multi-objective optimization: Application to environmental problems, Comput. Chem. Eng., 2011, vol. 35, pp. 1469–1477.

    Article  Google Scholar 

  42. Wang, F., Lai, X., and Shi, N., A multi-objective optimization for green supply chain network design, Decision Support Syst., 2011, vol. 51, pp. 262–269.

    Article  Google Scholar 

  43. Saffar, M.M., Shakouri, H.G., and Razmi, J., A new bi-objective mixed integer linear programming for designing a supply chain considering CO2 emission, Uncertain Supply Chain Manage., 2014, vol. 2, pp. 275–292.

    Article  Google Scholar 

  44. Saffar, M.M., Shakouri, H.G., and Razmi, J., A new multi objective optimization model for designing a green supply chain network under uncertainty, Int. J. Ind. Eng. Comput., 2015, vol. 6, pp. 15–32.

    Google Scholar 

  45. Messac, A., Ismail-Yahaya, A., and Mattson, C.A., The normalized normal constraint method for generating the Pareto frontier, Struct Multidisc Optim., 2003, vol. 25, pp. 86–98.

    Article  Google Scholar 

  46. Pishvaee, M. and Razmi, J., Environmental supply chain network design using multi-objective fuzzy mathematical programming, Appl. Math. Model., 2012, vol. 36, pp. 3433–3446.

    Article  Google Scholar 

  47. Pishvaee, M., Razmi, J., and Torabi, S., Robust possibilistic programming for socially responsible supply chain network design: A new approach, Fuzzy Sets Syst., 2012, vol. 206, pp. 1–20.

    Article  Google Scholar 

  48. Pishvaee, M., Torabi, S., and Razmi, J., Credibilitybased fuzzy mathematical programming model for green logistics design under uncertainty, Comput. Chem. Eng., 2012, vol. 62, pp. 624–632.

    Google Scholar 

  49. Cheng, L.C. and Lee, W.C., Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices, Comput. Chem. Eng., 2004, vol. 28, pp. 1131–1144.

    Article  Google Scholar 

  50. Kantyukov, R.A., Meshalkin, V.P., Panarin, V.M., Goriunkova, A.A., Gymranov, R.K., Ryzhenkov, I.V., and Kantyukov, P.P., Computer Model of atmospheric pollution in case of gasduct explosion, Neftegazov. Delo, 2015, vol. 13, pp. 90–96.

    Google Scholar 

  51. Alfaki, M. and Haugland, D., Strong formulations for the pooling problem, J. Global Optim., 2013, vol. 56, pp. 897–916.

    Article  Google Scholar 

  52. Kolodziej, S., Castro, P.M., and Grossmann, I.E., Global optimization of bilinear programs with a multiparametric disaggregation technique, J. Global Optim., 2013, vol. 57, pp. 1039–1063.

    Article  Google Scholar 

  53. Midthun, K.T., Mette, B., and Tomasgard, A., Modeling optimal economic dispatch and system effects in natural gas networks, Energy J., 2009, vol. 30, pp. 155–180.

    Article  Google Scholar 

  54. Kall, P. and Wallace, S.W., Stochastic Programming, Chichester: Wiley, 1994.

    Google Scholar 

  55. ICF Consulting Canada 2012. Life Cycle Greenhouse Gas Emissions of Natural Gas. http://www.capp.ca/~/media/capp/customer-portal/documents/215278.pdf. Accessed February 22, 2017.

  56. McCarl, B.A., Meeraus, A., van der Eijk, P., Bussieck, M., Dirkse, S., and Nelissen, F., McCarl Expanded GAMS User Guide. Version 24.6, Washington, DC: GAMS Development Corporation, 2016.

    Google Scholar 

  57. Makhorin, A., GUSEK (GLPK Under Scite Extended Kit) 2012. http://gusek.sourceforge.net/gusek.html. Accessed February 22, 2017.

    Google Scholar 

  58. Ferris, M.C., Dirkse, S.P., Jaglac, J.H., and Meeraus, A., An extended mathematical programming framework, Comput. Chem. Eng., 2009, vol. 33, pp. 1973–1982.

    Article  CAS  Google Scholar 

  59. Funaki, K., State of the Art Survey of Commercial Software for Supply Chain Design, Georgia Institute of Technology, 2009. http://tli.isye.gatech.edu/research/supplychain/GTSCL_scdesignsoftwaresurvey.pdf. Accessed February 22, 2017.

    Google Scholar 

  60. Kantyukov, R.A., Popov, A.G., Rizhenkov, I.V., Gimranov, R.K., Suharev, Mustafin, F.M., Modin, V.K., Meshalkin, V. P., Butusov, O. B., and Panarin, V.M., Experience of development of tatarstan republic gas pipeline systems energy and resource effective constructions with the use of polyethylene tubes, Modern High Technologies. Regional Application, 2015, no. 1, p. 112.

    Google Scholar 

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Authors and Affiliations

  1. Yenching Academy, University of Peking, Beijing, 100871, China

    Max-Sebastian Dovì

  2. Department of Logistics and Economic Informatics, Mendeleev University of Chemical Technology of Russia, Moscow, 125047, Russia

    Valery P. Meshalkin

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  1. Max-Sebastian Dovì
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  2. Valery P. Meshalkin
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Correspondence to Valery P. Meshalkin.

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Dovì, MS., Meshalkin, V.P. Mathematical Methods for the Multi-Criteria Optimization of Structure and Management of Energy Efficient Gas Supply Chains. Theor Found Chem Eng 51, 1080–1091 (2017). https://doi.org/10.1134/S0040579517060033

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