Skip to main content
SpringerLink
Log in

Worst-Case Modelling for Management Decisions under Incomplete Information, with Application to Electricity Spot Markets

  • Conference paper
Optimisation, Econometric and Financial Analysis

Part of the book series: Advances in Computational Management Science ((AICM,volume 9))

  • 2601 Accesses

Summary

Many economic sectors often collect significantly less data than would be required to analyze related standard decision problems. This is because the demand for some data can be intrusive to the participants of the economy in terms of time and sensitivity. The problem of modelling and solving decision models when relevant empirical information is incomplete is addressed. First, a procedure is presented for adjusting the parameters of a model which is robust against the worst-case values of unobserved data. Second, a scenario tree approach is considered to deal with the randomness of the dynamic economic model and equilibria is computed using an interior-point algorithm. This methodology is implemented in the Australian deregulated electricity market. Although a simplified model of the market and limited information on the production side are considered, the results are very encouraging since the pattern of equilibrium prices is forecasted

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bessembinder, H. and L. Lemmon. Equilibrium Pricing and Optimal Hedging in Electricity Forward Markets. The Journal of Finance, LVII:1347–1382, 2002.

    Article  Google Scholar 

  • Boucher, J. and Y. Smeers. Alternative models of restructured electricity systems, Part 1: No market power. Operations Research, 49:821–838, 2001.

    Article  Google Scholar 

  • Bounder, G. C. E. A hybrid simulation/optimisation scenario model for asset/liability management. European Journal of Operational Research, 99:126–135, 1997.

    Article  Google Scholar 

  • Bram, J. The Lagrange multiplier theorem for max-min with several constraints. SIAM J. Appl. Math., 14:665–667, 1966.

    Article  MATH  MathSciNet  Google Scholar 

  • Brockwell, P. J. and R. A. Davis. Time series: theory and methods. Springer Series in Statistics. Springer-Verlag, Berlin, Heidelberg New York Tokyo, 1987.

    Google Scholar 

  • Danskin, J. M. The Theory of Max-Min. Springer-Verlag, Berlin, Heidelberg New York Tokyo, 1967.

    MATH  Google Scholar 

  • Day, C. J., B. F. Hobbs and J.-S. Pang Oligopolistic Competition in Power Networks: A Conjectured Supply Function Approach. IEEE Trans. Power Systems, 17:597–607, 2002.

    Article  Google Scholar 

  • Escudero, L. F., J. L. de la Fuente, C. García and F.-J. Prieto Hydropower generation management under uncertainty via scenario analysis and parallel computation. IEEE Trans. Power Systems, 11:683–689, 1996.

    Article  Google Scholar 

  • Esteban-Bravo, M. Computing equilibria in general equilibrium models via interior-point method. Computational Economics, 23:147–171, 2004.

    Article  MATH  Google Scholar 

  • Green, R. Competition in Generation: The Economic Foundations. Proceedings of the IEEE, 88:128–139, 2000.

    Article  Google Scholar 

  • Gülpinar, N., B. Rustem and R. Settergren. Simulation and Optimisation Approaches to Scenario Tree Generation. Journal of Economics Dynamics and Control, 28:1291–1315, 2004.

    Article  Google Scholar 

  • Harvey, A. and S. J. Koopman. Forecasting Hourly Electricity Demand Using Time-Varying Splines. Journal of the American Statistical Association, 88:1228–1236, 1993.

    Article  Google Scholar 

  • Henley, A. and J. Peirson. Non-linearities in electricity demand and temperature: parametric versus non-parametric methods. Oxford Bulletin of Economics and Statistics, 59:149–162, 1997.

    Article  Google Scholar 

  • Hobbs, B. F. Network models of spatial oligopoly with an application to deregulation of electricity generation. Operations Research, 34:395–409, 1986.

    Article  Google Scholar 

  • Høyland, K., and S. W. Wallace Generating Scenario Tree for Multistage Decision Problems. Management Science, 47:295–307, 2001.

    Article  Google Scholar 

  • Hsu, M. An introduction to the pricing of electric power transmission. Utilities Policy, 6:257–270, 1997.

    Article  Google Scholar 

  • Jing-Yuan, W. and Y. Smeers. Spatial oligopolistic electricity models with Cournot generators and regulated transmission prices. Operations Research, 47:102–112, 1999.

    MATH  Google Scholar 

  • Kahn, E. P. Numerical Techniques for Analyzing Market Power in Electricity. The Electricity Journal, 11:34–43, 1998.

    Article  MathSciNet  Google Scholar 

  • Kouwenberg, R. Scenario generation and stochastic programming models for asset liability management. European Journal of Operational Research, 134:279–292, 2001.

    Article  MATH  MathSciNet  Google Scholar 

  • Mas-Colell, A., M. D. Whinston and J. R. Green. Microeconomic Theory. Oxford University Press, New York, 1995.

    Google Scholar 

  • McCalley, J. D. and G. B. Sheblé. Competitive electric energy systems: engineering issues in the great experiment. Tutorial paper presented at the 4th International Conference of Probabilistic Methods Applied to Power Systems, 1994.

    Google Scholar 

  • Neame P. J., A. B. Philpott and G. Pritchard. Offer stack optimisation in electricity pool markets. Operations Research, 51:397–408, 2003.

    Article  MathSciNet  Google Scholar 

  • Pardalos P. M. and G. C. Resende. Handbook of Applied Optimisation. Oxford University Press, New York, 2002.

    Google Scholar 

  • Pritchard, G. and Zakeri, G. Market Offering Strategies for Hydroelectric Generators. Operations Research, 51:602–612, 2003.

    Article  Google Scholar 

  • Rhys, J. M. W. Techniques for Forecasting Electricity Demand. Statistician, 33:23–33, 1984.

    Article  Google Scholar 

  • Rosen, J. B. Existence and uniqueness of equilibrium points for concave n-person games. Econometrica, 33:520–534, 1965.

    Article  MATH  MathSciNet  Google Scholar 

  • Rustem, B. and M. B. Howe. Algorithms for Worst-Case Design and Applications to Risk Management. Princeton University Press, Princeton and Oxford, 2002.

    MATH  Google Scholar 

  • Schweppe, F. C., M. C.Carmanis, R. B. Tabors and R. E. Bohn Spot Pricing of Electricity. Kluwer Academic Publishers, Boston, Mass., 1988.

    Google Scholar 

  • Sheblé, G. B. Decision Analysis Tools for GENCO Dispatchers. IEEE Transactions on Power Systems, 14:745–750, 1999.

    Article  Google Scholar 

  • Valenzuela, J. and M. Mazumdar. Statistical analysis of electric power production costs. IIE Transactions, 32:1139–1148, 2000.

    Article  Google Scholar 

  • Valenzuela, J. and M. Mazumdar. Making unit commitment decisions when electricity is traded at spot market prices. Proceedings of the 2001 IEEE Power Engineering Society Winter Meeting, Feb 01, Columbus, Ohio, 2001.

    Google Scholar 

  • Varian, H. Microeconomics Analysis. Norton, New York, 1992.

    Google Scholar 

  • Wright, M. H. Interior methods for constrained optimisation. Acta Numerica, 341–407, 1991.

    Google Scholar 

  • Žaković, S. and B. Rustem. Semi-infinite Programming and Applications to Minimax Problems. Annals of Operations Research, 124:81–110, 2003.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Business Administration, Universidad Carlos III de Madrid, Spain

    Mercedes Esteban-Bravo

  2. Department of Computing, Imperial College London, UK

    Berc Rustem

Authors
  1. Mercedes Esteban-Bravo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Berc Rustem
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Public and Business Administration, University of Cyprus, 75 Kallipoleos St, CY-1678 Nicosia, Cyprus

    Erricos John Kontoghiorghes

  2. Institut d’ Informatique, Université de Neuchatel, Rue Emile-Argand 11, CP2, CH-2007 Neuchatel, Switzerland

    Cristian Gatu

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Esteban-Bravo, M., Rustem, B. (2007). Worst-Case Modelling for Management Decisions under Incomplete Information, with Application to Electricity Spot Markets. In: Kontoghiorghes, E.J., Gatu, C. (eds) Optimisation, Econometric and Financial Analysis. Advances in Computational Management Science, vol 9. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36626-1_2

Download citation

  • DOI: https://doi.org/10.1007/3-540-36626-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36625-6

  • Online ISBN: 978-3-540-36626-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation