Finding Joint Bidding Strategies for Day-Ahead Electricity and Related Markets

  • Patricio Rocha
  • Tapas K. Das
Part of the Energy Systems book series (ENERGY)


In restructured electricity markets, generators and other market participants submit bids to the system operator, who dispatches power while satisfying the system constraints. Dispatch establishes the market clearing price for electricity at each node of the network. In recent years, power market participants have begun competing in electricity-related markets for financial instruments such as financial transmission rights (FTRs) and CO 2 allowances. Benefits derived from these markets depend largely on the electricity dispatch. For example, payments received by FTR holders are determined by the differential market clearing price between the nodes; CO 2 allowances needed by the generators depend on the amount of fossil fuel-based electricity dispatched in the network. Hence, the participants must develop bidding strategies that maximize their joint profits from electricity and other related markets. This chapter, presents a multi-tier game theoretic framework that can be used to develop joint bidding strategies. In the electricity market, we focus on day-ahead and spot market bidding. Though there are many market participants (generators, loads, and third parties), the framework presented in this chapter caters directly to the needs of the generators. The multi-player matrix games underlying the framework are solved using an approach that incorporates a reinforcement learning algorithm. Application of the framework is exemplified via three example problems.


Bidding strategies Cap and trade CO2 allowance FTRs Matrix games Restructured electricity markets 



This research was supported in part by a grant from the Florida Energy Systems Consortium (FESC), 2009–2011.


  1. 1.
    Alvarado FL, Oren SS (2000) A tutorial on the flowgates versus nodal pricing debate. In: PSERC IAB Meeting, 2000Google Scholar
  2. 2.
    Arthur WB (2006) Out-of-equilibrium economics and agent-based modeling. In: Judd KL, Tesfatsion L (eds) Handbook of computational economics, vol 2. Elsevier/North-Holland, Amsterdam, pp 1551–1564Google Scholar
  3. 3.
    Babayigit C, Rocha P, Das TK (2010) A two-tier matrix game approach for obtaining joint bidding strategies in FTR and energy markets. IEEE Trans Power Syst 25:1211–1219CrossRefGoogle Scholar
  4. 4.
    Bautista G, Quintana VH (2005) Screening and mitigation of exacerbated market power due to nancial transmission rights. IEEE Trans Power Syst 20:213–222CrossRefGoogle Scholar
  5. 5.
    Berry CA, Hobbs BF, Meroney WA, O’Neill RP, Stewart WR Jr (1999) Understanding how market power can arise in network competition: a game theoretic approach. Utilities Policy 8:139–158CrossRefGoogle Scholar
  6. 6.
    Bhattacharya K, Bollen MHJ, Daalder JE (2001) Operation of restructured power systems. Kluwer, BostonCrossRefGoogle Scholar
  7. 7.
    Budhraja V, Woolf F (1994) Poolco: an independent power pool company for an efficient market. Electr J 7:42–47CrossRefGoogle Scholar
  8. 8.
    Burtraw D (2006) CO 2 allowance allocation in the Regional Greenhouse Gas Initiative and the effect on electricity investors. Electr J 19:79–90CrossRefGoogle Scholar
  9. 9.
    Burtraw D, Sweeney R, Walls M (2008) The incidence of US climate policy: where you stand depends on where you sit. DP 08–28. Resources for the Future, Washington, DCGoogle Scholar
  10. 10.
    Chuang AS, Wu F, Varaiya P (2001) A game-theoretic model for generation expansion planning: problem formulation and numerical comparisons. IEEE Trans Power Syst 16:885–891CrossRefGoogle Scholar
  11. 11.
    Das TK, Rocha P, Babayigit C (2010) A matrix game model for analyzing FTR bidding strategies in deregulated electric power markets. Int J Electr Power Energy Syst 32:760–768CrossRefGoogle Scholar
  12. 12.
    Department of Energy, EIA.
  13. 13.
    Garber D, Hogan B, Ruff L (1994) Poolco: an efficient electricity market: using a pool to support real competition. Electr J 7:48–60CrossRefGoogle Scholar
  14. 14.
    General Accounting Office US (2002) Lessons learned from electricity restructuring: Report to congressional requesters. Technical Report GAO-03-271. General Accounting Office, Washington, DCGoogle Scholar
  15. 15.
    Hobbs BF (2001) Linear complementarity models of NashCournot competition in bilateral and poolco power markets. IEEE Trans Power Syst 16:194–202CrossRefGoogle Scholar
  16. 16.
    Hobbs BF, Metzler CB, Pang JS (2000) Strategic gaming analysis for electric power systems: an MPEC approach. IEEE Trans Power Syst 15:638–645CrossRefGoogle Scholar
  17. 17.
    Hogan WW (2002) Financial transmission right formulations. Technical Report. Harvard University, Cambridge, MAGoogle Scholar
  18. 18.
    Joskow PL (2008) Lessons learned from electricity market liberalization. Energy J 29:9–42Google Scholar
  19. 19.
    Joskow PL, Tirole J (2000) Transmission rights and market power on electric power networks. RAND J Econ 31:450–487CrossRefGoogle Scholar
  20. 20.
    Kirby BJ, Van Dyke JW (2002) Congestion management requirements, methods and performance indices. Technical report ORNL/TM-2002/119. Oak Ridge National Laboratory, Oak RidgeGoogle Scholar
  21. 21.
    Kirschen D, Strbac G (2005) Basic concepts from economics, in fundamentals of power system economics. Wiley, Chichester. doi: 10.1002/0470020598.ch2 Google Scholar
  22. 22.
    Kirschen D, Strbac G (2005) Transmission networks and electricity markets, in fundamentals of power system economics. Wiley, Chichester. doi: 10.1002/0470020598.ch6 Google Scholar
  23. 23.
    Lee KH, Baldick R (2003) Tuning of discretization in bimatrix game approach to power system market analysis. IEEE Trans Power Syst 18:830–836CrossRefGoogle Scholar
  24. 24.
    Li T, Shahidehpour M (2005) Risk-constrained FTR bidding strategy in transmission markets. IEEE Trans Power Syst 20:1014–1021CrossRefGoogle Scholar
  25. 25.
    Linares P, Santos FJ, Ventosa M, Lapiedra L (2008) Incorporating oligopoly, CO 2 emissions trading and green certificates into a power generation expansion model. Automatica 44:1608–1620MathSciNetCrossRefGoogle Scholar
  26. 26.
    Murphy F, Smeers Y (2005) Generation capacity expansion in imperfectly competitive restructured electricity markets. Oper Res 53:646–661CrossRefzbMATHGoogle Scholar
  27. 27.
    Nanduri N, Das TK (2007) A reinforcement learning model to assess market power under auction-based energy pricing. IEEE Trans Power Syst 22:85–95CrossRefGoogle Scholar
  28. 28.
    Nanduri N, Das TK (2009) A survey of critical research areas in the energy segment of restructured electricity markets. Electr Power Energy Syst 31:181–191CrossRefGoogle Scholar
  29. 29.
    Nanduri N, Das TK (2009) A reinforcement learning approach to obtain Nash equilibria of multiplayer matrix games. IIE Trans Oper Eng 41:158–167CrossRefGoogle Scholar
  30. 30.
    Nanduri V, Das TK, Rocha P (2009) Generation capacity expansion in energy markets using a two-level game theoretic model. IEEE Trans Power Syst 24:1165–1172CrossRefGoogle Scholar
  31. 31.
    O’Neill RP, Helman U, Hobbs BF, Stewart WR Jr, Rothkopf MH (2002) A joint energy and transmission rights auction: proposal and properties. IEEE Trans Power Syst 17:1058–1067CrossRefGoogle Scholar
  32. 32.
    Paltsev S, Reilly JM, Jacoby HD, Gurgel AC, Metcalf GE, Sokolov AP, Holak JF (2007) Assessment of US cap-and-trade proposals. No. 13176. National Bureau of Economic Research, Cambridge, MAGoogle Scholar
  33. 33.
  34. 34.
  35. 35.
    Ragupathi R, Das TK (2004) Stochastic game approach for modeling wholesale energy bidding in deregulated power markets. IEEE Trans Power Syst 19:849–856CrossRefGoogle Scholar
  36. 36.
    Regional Greenhouse Gas Initiative, RGGI.
  37. 37.
    Rocha P, Das TK, Nanduri V, Botterud A (2010) Generation capacity expansion in restructured power markets under a CO 2 cap-and-trade program. In reviewGoogle Scholar
  38. 38.
    Ruth M, Gabriel SA, Palmer KL, Burtraw D, Paul A, Chen Y, Hobbs BF, Irani D, Michael J, Ross KM, Conklin R, Miller J (2008) Economic and energy impacts from participation in the regional greenhouse gas initiative: a case study of the state of Maryland. Energy Policy 36:2279–2289CrossRefGoogle Scholar
  39. 39.
    Son YS, Baldick R, Lee K, Siddiqi S (2004) Short-term electricity market auction game analysis: uniform and pay-as-bid pricing. IEEE Trans Power Syst 19:1990–1998CrossRefGoogle Scholar
  40. 40.
    Su CL (2005) Equilibrium problems with equilibrium constraints: stationarities, algorithms, and applications. Dissertation from the Department of Management Sciences, Stanford UniversityGoogle Scholar
  41. 41.
    Yao J (2006) Cournot equilibrium in two settlement electricity markets: formulation and computation. Dissertation, University of California, BerkeleyGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Patricio Rocha
    • 1
  • Tapas K. Das
    • 2
  1. 1.PJM InterconnectionNorristownUSA
  2. 2.University of South FloridaTampaUSA

Personalised recommendations