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A model for optimization of transport infrastructure for some homogeneous goods markets

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Abstract

The optimization problem studied in this paper generalizes the standard transportation problem and turns out to be NP-hard under the positive fixed costs of the transmission lines expansion. For a market with a tree-type network, a method for the supply-demand balances transfer to its root node is proposed. The method is based on the Welfare Theorem, and it proceeds from a solution to an auxiliary convex optimization problem with zero fixed costs for the lines expansion. The complexity of the method for the auxiliary problem is proven to be quadratic with respect to the number of nodes. Also, the proposed method is modified to obtain an approximate solution to the original problem and to estimate the welfare loss corresponding to this solution.

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References

  1. Davidson, M.R., Dogadushkina, Y.V., Kreines, E.M., Novikova, N.M., Seleznev, A.V., Udaltsov, Y.A., Shiryaeva, L.V.: Mathematical model of power system management in conditions of a competitive wholesale electric power (capacity) market in Russia. J. Comput. Syst. Sci. Int. 48, 243–253 (2009)

    Article  Google Scholar 

  2. Edoli, E., Fiorenzani, S., Vargiolu, T.: Optimization Methods for Gas and Power Markets: Theory and Cases, XVII, 192. Palgrave Macmillan, Basingstoke (2016)

    Book  Google Scholar 

  3. Hogan, W.: Competitive Electricity Market Design: A Wholesale Primer. Technical Report. Harvard Electricity Policy Group (1998)

  4. Wu, F., Harsha, N., Zlotnik, A., Sioshansi, R., Rudkevich, A.M.: Adaptive convex relaxations for gas pipeline network optimization. In: IEEE Conference Proceedings, vol. 2017, pp. 4710–4716 (2017)

  5. Roger, Z.R.-M., Conrado, B.-S.: Optimization problems in natural gas transportation systems: a state-of-the-art review. Appl. Energy 147(1), 536–555 (2015)

    Google Scholar 

  6. Gomes, P.V., Saraiva, J.T.: Hybrid genetic algorithm for multi-objective transmission expansion planning. In: IEEE International Energy Conference (ENERGYCON), Belgium, April 4–8 (2016)

  7. Zhao, H.-S., Chen, L., Wu, T.: Optimal computation of the transmission system expansion planning using the branch and bound method. In: Asia-Pacific Power and Energy Engineering Conference (2009)

  8. Choi, J., Tran, T., El-Keib, A.A., Thomas, R., Oh, H.S., Billinton, R.: A method for transmission system expansion planning considering probabilistic reliability criteria. IEEE Trans. Power Syst. 20(3), 1606–1615 (2005)

    Article  Google Scholar 

  9. Soleimani, K., Mazloum, J.: Considering FACTS in optimal transmission expansion planning engineering. Technol. Appl. Sci. Res. 7(5), 1987–1995 (2017)

    Google Scholar 

  10. Jabr, R.A.: Optimization of AC transmission system planning. IEEE Trans. Power Syst. 28(3), 2779–2787 (2013)

    Article  Google Scholar 

  11. Daylova, E.A., Vasin, A.A.: Determination of transmission capacity for a two-node market. Proc. Comput. Sci. 31, 151–157 (2014)

    Article  Google Scholar 

  12. Vasin, A.A., Grigoryeva, O.M., Tsyganov, N.I.: Optimization of an energy market transportation system. Dokl. Math. 96(1), 1–4 (2017)

    Article  Google Scholar 

  13. Arrow, K.J., Debreu, G.: Existence of an equilibrium for a competitive economy. Econometrica 22, 265–290 (1954)

    Article  MathSciNet  Google Scholar 

  14. Kantorovich, L.V., Gavurin, M.K.: Application of mathematical methods in the analysis of cargo flows. In: Problems of Increasing the Efficiency of Transport. M.: Publishing House of AN USSR, pp. 110–138 (the work was written in 1940, in Russian) (1949)

  15. Guisewite, G.M., Pardalos, P.M.: Minimum concave-cost network flow problems: applications, complexity, and algorithms. Ann. Oper. Res. 25(1), 75–99 (1990)

    Article  MathSciNet  Google Scholar 

  16. Kleinberg, J., Tardos, E.: Algorithm Design. Pearson Education, London (2006)

    Google Scholar 

  17. Khachaturov, V.R.: Mathematical Methods of Regional Programming. Nauka, Moscow (1989). (in Russian)

    MATH  Google Scholar 

  18. Mas-Colell, A., Whinston, M.D., Green, J.R.: Microeconomic Theory, p. 133. Oxford University Press, New York (1995)

    MATH  Google Scholar 

  19. Stoft, S.: Power System Economics: Designing Markets for Electricity. Wiley, New York (2002)

    Book  Google Scholar 

  20. Vasin, A., Dolmatova, M.: Optimization of transmission capacities for multinodal markets. Proc. Comput. Sci. 91, 238–244 (2016)

    Article  Google Scholar 

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Acknowledgements

A preliminary version of this paper was presented at XVII Baikal International School-Seminar and ORM 2018 conference. We thank the participants, as well as our referees, for useful comments.

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Correspondence to Olesya Grigoryeva.

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This research is supported by RFBR 19-01-00533a.

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Vasin, A., Grigoryeva, O. & Tsyganov, N. A model for optimization of transport infrastructure for some homogeneous goods markets. J Glob Optim 76, 499–518 (2020). https://doi.org/10.1007/s10898-019-00785-y

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  • DOI: https://doi.org/10.1007/s10898-019-00785-y

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