Advertisement

An LP Based Market Design for Natural Gas

  • E. G. ReadEmail author
  • B. J. Ring
  • S. R. Starkey
  • W. Pepper
Chapter
Part of the Energy Systems book series (ENERGY)

Abstract

Many electricity markets are now cleared using Linear Programming (LP) formulations that simultaneously determine an optimal dispatch and corresponding nodal prices, for each market dispatch interval. Although natural gas markets have traditionally operated in a very different fashion, the same basic concept can be applied. Since 1999, the Australian state of Victoria has operated a gas market based on an LP approximation to the underlying gas flow optimization problem. Here we discuss market design issues, using a formulation derived from the key gas flow equations. Dual variables on key constraints imply prices which vary by location, as for electricity markets, but also by time. But gas is both delayed and stored within the transportation system itself. This raises a number of operational, pricing, and hedging issues which could be ignored in the case of electricity, but become important when operating this kind of market for gas, or other commodities, such as water, in a supply network where there are delays and storage.

Keywords

Linear Programming (LP) Linearization Market Natural gas Optimization Pipelines Prices 

References

  1. 1.
    AEMO (2010) A technical guide to the Victorian gas wholesale market. http://www.aemo.com.au/corporate/0000-0264_OnlinePDF.pdf. Accessed 7 Aug 2010
  2. 2.
    Alvey T, Goodwin D, Ma X, Streiffert D, Sun D (1998) A security-constrained bid-clearing system for the New Zealand wholesale electricity market. IEEE Trans Power Syst 13(2):340–346CrossRefGoogle Scholar
  3. 3.
    Boyd SP, Vandenberghe L (2004) Convex optimization. Cambridge University Press, New YorkCrossRefGoogle Scholar
  4. 4.
    Breton N, Zaccour Z (2001) Equilibria in an asymmetric duopoly facing a security constraint. Energ Econ 25:457–475CrossRefGoogle Scholar
  5. 5.
    Chao H, Peck S, Oren S, Wilson R (2000) Flow-based transmission rights and congestion management. Electric J 13(8):38–58CrossRefGoogle Scholar
  6. 6.
    Cremer H, Gasmi F, Laffont JJ (2003) Access to pipelines in competitive gas markets. J Regul Econ 24(1):5–33CrossRefGoogle Scholar
  7. 7.
    De Wolf D, Smeers Y (1997) A stochastic version of a Stackelberg Nash-Cournot equilibrium model. Manag Sci 43(2):190–197CrossRefGoogle Scholar
  8. 8.
    Doane MJ, Spulber DF (1994) Open access and the evolution of the US spot market for natural gas. JLE 37(2):477–517CrossRefGoogle Scholar
  9. 9.
    Dorin B, Toma-Leonida D (2008) On modelling and simulating natural gas transmission systems (Part I). J Control Eng Appl Inform 10(3):27Google Scholar
  10. 10.
    DPI: Victorian Government Department of Primary Industries (2009) The Victorian gas market. http://new.dpi.vic.gov.au/earth-resources/industries/oil-gas/petroleum-explorers-guide-to-victoria/the-victorian-gas-market. Accessed 2 Sep 2010
  11. 11.
    Frontier Economics (2003) Analysis of high level design directions for the Victorian gas market. Report to VENCorpGoogle Scholar
  12. 12.
    Gabriel SA, Manik J, Vikas S (2003) Computational experience with a large-scale, multi period, spatial equilibrium model of the North America natural gas system. Netw Spat Econ 3:97–122CrossRefGoogle Scholar
  13. 13.
    Gabriel SA, Kiet S, Zhuang J (2005) A mixed complementarity-based equilibrium model of natural gas markets. Oper Res 53(5):799–818MathSciNetCrossRefGoogle Scholar
  14. 14.
    Gilbert RJ, Kahn EP (1996) International comparisons of electricity regulation. Cambridge University Press, Cambridge, UKCrossRefGoogle Scholar
  15. 15.
    Hogan WW (1992) An Efficient Concurrent Auction Model for Firm Natural Gas Transportation Capacity. Information Systems and Operational Research, Vol 30, No. 3Google Scholar
  16. 16.
    Hogan WW, Read EG, Ring BJ (1996) Using mathematical programming for electricity spot pricing. Int Trans Oper Res 3(4):209–221CrossRefGoogle Scholar
  17. 17.
    Johnson RB, Oren SS, Svoboda AJ (1997) Equity and efficiency of unit commitment in competitive electricity markets. Utilities Policy 6(1):9–19CrossRefGoogle Scholar
  18. 18.
    McCabe KA, Rassenti SJ, Smith VL (1989) Designing ‘smart’ computer-assisted markets: an experimental auction for gas networks. Eur J Polit Econ 5(2–3):259–283CrossRefGoogle Scholar
  19. 19.
    Martin A, Moller M, Moritz S (2006) Mixed integer models for the stationary case of gas network optimization. Math Program Ser B 105:563–582MathSciNetCrossRefGoogle Scholar
  20. 20.
    Midthun KT, Bjørndal M, Tomasgard A, Smeers Y (2007) Paper IV Capacity booking in a Transportation Network with stochastic demand and a secondary market for Transportation Capacity. www.iot.ntnu.no/winterschool11/web/material/tomasgard_paper_OnlinePDF.pdf. Accessed 27 Nov 2011
  21. 21.
    Midthun KT, Bjørndal M, Tomasgard A (2009) Modeling optimal economic dispatch and system effects in natural gas networks. Energy J 30(4):155–180CrossRefGoogle Scholar
  22. 22.
    Modisette J, Modisette J (2003) Physics of pipeline flow: energy solutions. www.energy-solutions.com/pdf/tech_paper_Modisette_Physics_of_Pipeline_Flow_OnlinePDF.pdf. Accessed 11 July 2010
  23. 23.
    Murphy JJ, Dinar A, Howitt RE, Rassenti SJ, Smith VL (2000) The design of “smart” water market institutions using laboratory experiments. Environ Resour Econ 17(4):375–394CrossRefGoogle Scholar
  24. 24.
    O’Neil RP, Williard M, Wilkins B, Pike R (1979) A mathematical programming model for allocation of natural gas. Oper Res 27(5):857–873CrossRefGoogle Scholar
  25. 25.
    Pepper W (2002) Stage 2-evaluation of market design packages: detailed report. Report by ICF Consulting and Pacific Economics Group to VENCorpGoogle Scholar
  26. 26.
    Pepper W, Ring BJ, Read EG Starkey SR (2012) Implementation of a scheduling and pricing model for natural gas. A. Sorokin et al. (eds.), Handbook of Networks in Power Systems II, Energy Systems, Springer-Verlag Berlin HeidelbergGoogle Scholar
  27. 27.
    Prabodanie RA, Raffensperger JF, Milke MW (2009) Simulation-optimization approach for trading point and non-point source nutrient permits. Paper presented at the 18th World IMACS congress and MODSIM09 international congress on modelling and simulation, Cairns, Australia, 13–17 July 2009Google Scholar
  28. 28.
    Raffensperger JF, Milke MW, Read EG (2009) A deterministic smart market model for groundwater. Oper Res 57(6):1333–1346CrossRefGoogle Scholar
  29. 29.
    Read EG (1989) Pricing and operation of transmission services: long run aspects. In: Turner A (ed) Principles for pricing electricity transmission. Trans Power New Zealand, Wellington, NZGoogle Scholar
  30. 30.
    Read EG (1997) Transmission pricing in New Zealand. Utilities Policy 6(3):227–236CrossRefGoogle Scholar
  31. 31.
    Read EG (2010) Co-optimization of energy and ancillary service markets. In: Rebennack IS, Pardalos PM, Pereira MVF, Iliadis NA (eds) Handbook of power systems. Springer-Verlag Berlin Heidelberg, pp 307–327CrossRefGoogle Scholar
  32. 32.
    Read EG, Whaley R (1997) A gas market model for Victoria: dispatch/pricing formulation. Report by Putnam, Hayes & Bartlett–Asia Pacific Ltd. to VENCorpGoogle Scholar
  33. 33.
    Ring BJ, Read EG (1996) A dispatch based pricing model for the New Zealand electricity market. In: Einhorn MA, Siddiqi R (eds) Electricity transmission pricing and technology. Kluwer Academic, Boston, pp 183–206Google Scholar
  34. 34.
    Rudnick H, Palma R, Fernandez JE (1995) Marginal pricing and supplement cost allocation in transmission open access. IEEE Tran Power Syst 10(2):1125–1132CrossRefGoogle Scholar
  35. 35.
    Ruff LE (1997) Victorian gas market clearing logic. Report by Putnam, Hayes & Bartlett Asia Pacific Ltd to VENCorpGoogle Scholar
  36. 36.
    Sioshansi F, Pfaffenberger W (2006) Electricity market reform: an international perspective. Elsevier, AmsterdamGoogle Scholar
  37. 37.
    Vany AS, De Walls WD (1994) Open access and the emergence of a competitive natural gas market. Contemp Econ Policy 12(2):77–96CrossRefGoogle Scholar
  38. 38.
    Tomasgard A, Rømo F, Fodstad M, Midthun KT (2007) Optimization models for the natural gas value chain, In: Hasle G, Lie KA, Quak E (eds) Geometric modelling, numerical simulation, and optimization: applied mathematics at SINTEF, Springer-Verlag, Berlin Heidelberg, pp 521–558CrossRefGoogle Scholar
  39. 39.
    Wolak FA (2000) An empirical analysis of the impact of hedge contracts on bidding behavior in a competitive electricity market. Int Econ J 14(2):1–39MathSciNetCrossRefGoogle Scholar
  40. 40.
    Zheng QP, Rebennack S, Iliadis N, Pardalos PM (2010) Optimization models in the natural gas industry. In: Rebennack IS, Pardalos PM, Pereira MVF, Iliadis NA (eds) Handbook of power systems. Springer-Verlag Berlin Heidelberg, pp 121–148CrossRefGoogle Scholar
  41. 41.
    Zhou J, Adewumi MA (1990) The development and testing of a new flow equation: the Pennsylvania State University. www.psig.org/papers/1990/9504_OnlinePDF.pdf. Accessed 1 Feb 2011
  42. 42.
    Energy Projects Division (EPD), Dept. of Treasury & Finance, (1998) Victoria’s Gas Industry: Implementing a competitive Structure. Information Paper No. 3, 2nd Edition, AprilGoogle Scholar
  43. 43.
    McCabe KA, Rassenti SJ, Smith VL (1990) Auction Design for Composite Goods: The Natural Gas Industry. Journal of Economic Behavior and Organization 14:127–149. Elsevier Science, North-HollandCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • E. G. Read
    • 1
    Email author
  • B. J. Ring
    • 2
  • S. R. Starkey
    • 1
  • W. Pepper
    • 3
  1. 1.University of CanterburyChristchurchNew Zealand
  2. 2.Market ReformSydneyAustralia
  3. 3.ICF InternationalFairfaxUSA

Personalised recommendations