Advertisement

Short-Term Electricity Market Prices: A Review of Characteristics and Forecasting Methods

  • Hamid Zareipour
Chapter
Part of the Energy Systems book series (ENERGY)

Abstract

In this chapter, short-term electricity price modeling and forecasting in competitive electricity markets is presented. Dominant characteristics of short-term electricity prices such as, seasonality, non-stationarity, spikes and volatility are discussed and numerical examples from real-life markets are presented. A review of the existing literature on short-term electricity price forecasting is also provided, followed by an overview of the process of building data-driven models for electricity prices. Furthermore, some popular time series models for electricity market price modeling and forecasting, such as ARIMA models, are discussed. A case study is also presented in which Ontario electricity market prices are modeled and 24-h-ahead forecast are generated.

Keywords

Artificial intelligence Competitive prices Electricity market Price forecasting Price volatility Time series models 

References

  1. 1.
    Bhattacharya K, Bollen MH, Dallder JE (2001) Operation of restructured power systems. Kluwer, BostonCrossRefGoogle Scholar
  2. 2.
    Conejo AJ, Nogales FJ, Arroyo JM (2002) Price-taker bidding strategy under price uncertainty. IEEE Trans Power Syst 17(4):1081–1088CrossRefGoogle Scholar
  3. 3.
    Vehvilinen I, Keppo J (2003) Managing electricity market price risk. Eur J Oper Res 145(1):136–147CrossRefGoogle Scholar
  4. 4.
    Conejo A, Garcia-Bertrand R, Diaz-Salazar M (2005) Generation maintenance scheduling in restructured power systems. IEEE Trans Power Syst 20(2):984–992CrossRefGoogle Scholar
  5. 5.
    Nogales FJ, Contreras J, Conejo AJ, Espinola R (2002) Forecasting next-day electricity prices by time series models. IEEE Trans Power Syst 17(2):342–348CrossRefGoogle Scholar
  6. 6.
    Huisman R, Mahieu RJ (2003) Regime jumps in electricity prices. Energ Econ 25(5):425–434CrossRefGoogle Scholar
  7. 7.
    Ruibal C, Mazumdar M (2008) Forecasting the mean and the variance of electricity prices in deregulated markets. IEEE Trans Power Syst 23(1):25–32CrossRefGoogle Scholar
  8. 8.
    Gonzalez AM, Roque AMS, Garcia-Gonzalez J (2005) Modeling and forecasting electricity prices with input/output hidden Markov models. IEEE Trans Power Syst 20(1):13–24CrossRefGoogle Scholar
  9. 9.
    Niimura T (2006) Forecasting techniques for deregulated electricity market prices - extended survey. In: 2006 IEEE PES power systems conference and exposition PSCE’06, Atlanta, 2006, pp 51–56Google Scholar
  10. 10.
    Vehviläinen I, Pyykkönen T (2005) Stochastic factor model for electricity spot price–the case of the nordic market. Energ Econ 27(2):351–367, special Issue on Electricity MarketsCrossRefGoogle Scholar
  11. 11.
    Zareipour H, Canizares C, Bhattacharya K, Thomson J (2006) Application of public-domain market information to forecast Ontario wholesale electricity prices. IEEE Trans Power Syst 21(4):1707–1717CrossRefGoogle Scholar
  12. 12.
    Weron R (2006) Modeling and forecasting electricity loads and prices: a statistical approach. Wiley, ChichesterCrossRefGoogle Scholar
  13. 13.
    Zareipour H, Canizares CA, Bhattacharya K (2007) The operation of Ontario’s competitive electricity market: overview, experiences, and lessons. IEEE Trans Power Syst 22(4):1782–1793CrossRefGoogle Scholar
  14. 14.
    Box GEP, Jenkins GM, Reinsel GC (1994) Time series analysis, forecasting and control. Prentice Hall, Englewood CliffszbMATHGoogle Scholar
  15. 15.
    Zhao JH, Dong ZY, Li X, Wong KP (2007) A framework for electricity price spike analysis with advanced data mining methods. IEEE Trans Power Syst 22(1):376–385CrossRefGoogle Scholar
  16. 16.
    AESO (2009) The Alberta electric system operator (AESO). http://www.aeso.ca/
  17. 17.
    Li Y, Flynn PC (2004) Deregulated power prices: comparison of volatility. Energ Policy 32(14):1591–1601CrossRefGoogle Scholar
  18. 18.
    Zareipour H, Bhattacharya K, Canizares C (2007) Electricity market price volatility: the case of Ontario. Energ Policy 35(9):4739–4748CrossRefGoogle Scholar
  19. 19.
    Simonsen I (2005) Volatility of power markets. Phys A Stat Mech Appl 335(1):10–20MathSciNetCrossRefGoogle Scholar
  20. 20.
    Amjady N, Keynia F (2009) Day-ahead price forecasting of electricity markets by mutual information technique and cascaded neuro-evolutionary algorithm. IEEE Trans Power Syst 24(1):306–318CrossRefGoogle Scholar
  21. 21.
    Lora A, Santos J, Exposito A, Ramos J, Santos J (2007) Electricity market price forecasting based on weighted nearest neighbors techniques. IEEE Trans Power Syst 22(3):1294–1301CrossRefGoogle Scholar
  22. 22.
    Bompard E, Ciwei G, Napoli R, Torelli F (2007) Dynamic price forecast in a competitive electricity market. IET Gener Transm Distrib 1(5):776–783CrossRefGoogle Scholar
  23. 23.
    Weron R, Misiorek A (2008) Forecasting spot electricity prices: a comparison of parametric and semiparametric time series models. Int J Forecast 24(4):744–763CrossRefGoogle Scholar
  24. 24.
    Fan S, Mao C, Chen L (2007) Next-day electricity-price forecasting using a hybrid network. IET Gener Transm Distrib 1(1):176–182CrossRefGoogle Scholar
  25. 25.
    Rodriguez CP, Anders GJ (2004) Energy price forecasting in the Ontario competitive power system market. IEEE Trans Power Syst 19(1):366–374CrossRefGoogle Scholar
  26. 26.
    Aggarwal S, Saini L, Kumar A (2009) Day-ahead price forecasting in Ontario electricity market using variable-segmented support vector machine-based model. Electr Power Compon Syst 37(5):495–516CrossRefGoogle Scholar
  27. 27.
    Saini L, Aggarwal S, Kumar A (2010) Parameter optimisation using genetic algorithm for support vector machine-based price-forecasting model in national electricity market. IET Gener Transm Distrib 4(1):36–49CrossRefGoogle Scholar
  28. 28.
    Taylor J, McSharry P (2007) Short-term load forecasting methods: an evaluation based on European data. IEEE Trans Power Syst 22(4):2213–2219CrossRefGoogle Scholar
  29. 29.
    Ipakchi A, Albuyeh F (2009) Grid of the future. IEEE Power Energ Mag 7(2):52–62CrossRefGoogle Scholar
  30. 30.
    Zhang L, Luh P (2005) Neural network-based market clearing price prediction and confidence interval estimation with an improved extended Kalman filter method. IEEE Trans Power Syst 20(1):59–66CrossRefGoogle Scholar
  31. 31.
    Zhao JH, Dong ZY, Xu Z, Wong KP (2008) A statistical approach for interval forecasting of the electricity price. IEEE Trans Power Syst 23(2):267–276CrossRefGoogle Scholar
  32. 32.
    Boogert A, Dupont D (2008) When supply meets demand: the case of hourly spot electricity prices. IEEE Trans Power Syst 23(2):389–398CrossRefGoogle Scholar
  33. 33.
    Zareipour H, Janjani A, Leung H, Motamedi A, Schellenberg A (2011) Classification of future electricity market prices. IEEE Transactions on Power System 26(1):165–173Google Scholar
  34. 34.
    Conejo AJ, Plazas MA, Espinola R, Molina AB (2005) Day-ahead electricity price forecasting using the wavelet transform and ARIMA models. IEEE Trans Power Syst 20(2):1035–1042CrossRefGoogle Scholar
  35. 35.
    Han J, Kamber M (2006) Data mining: concepts and techniques, The Morgan Kaufmann series in data management systems. Morgan Kaufmann, AmsterdamGoogle Scholar
  36. 36.
    Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques. Morgan Kaufmann, AmsterdamGoogle Scholar
  37. 37.
    Saeys Y, Inza I, Larranaga P (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23(19):2507–2517CrossRefGoogle Scholar
  38. 38.
    Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182zbMATHGoogle Scholar
  39. 39.
    Dash M, Liu H (1997) Feature selection for classification. Intell Data Anal 1(3):131–156CrossRefGoogle Scholar
  40. 40.
    Li G, Liu CC, Mattson C, Lawarree J (2007) Day-ahead electricity price forecasting in a grid environment. IEEE Trans Power Syst 22(1):266–274CrossRefGoogle Scholar
  41. 41.
    Contreras J, Espinola R, Nogales F, Conejo A (2003) ARIMA models to predict next-day electricity prices. IEEE Trans Power Syst 18(3):1014–1020CrossRefGoogle Scholar
  42. 42.
    Pindoriya N, Singh S, Singh S (2008) An adaptive wavelet neural network-based energy price forecasting in electricity markets. IEEE Trans Power Syst 23(3):1423–1432CrossRefGoogle Scholar
  43. 43.
    Zareipour H, Bhattacharya K, Canizares C(2006) Forecasting the hourly Ontario energy price by multivariate adaptive regression splines. In: Proceedings of the IEEE PES Annual General Meeting, San Francisco, 2006, p 7Google Scholar
  44. 44.
    Conejo AJ, Contreras J, Esanola R, Plazas MA (2005) Forecasting electricity prices for a day-ahead pool-based electric energy market. Int J Forecast 21(3):435–462CrossRefGoogle Scholar
  45. 45.
    Zareipour H, Canizares C, Bhattacharya K (2010) Economic impact of electricity market price forecasting errors: a demand-side analysis. IEEE Trans Power Syst 25(1):254–262CrossRefGoogle Scholar
  46. 46.
    Pankratz A (1991) Forecasting with dynamic regression models. Wiley, New YorkCrossRefGoogle Scholar
  47. 47.
    MSP (2011) Monitoring reports on the IESO-administered electricity markets, The Market Surveillance Panel, Ontario, 2002–2005. www.ieso.ca/imoweb/marketSurveil/mspReports.asp

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hamid Zareipour
    • 1
  1. 1.University of CalgaryCalgaryCanada

Personalised recommendations