Forecasting system imbalance volumes in competitive electricity markets

IEEE Transactions on Power Systems

Volumn 21, Issue 1, 2006, Pages 240-248

  Garcia, Maria P ^a   Kirschen, Daniel S ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

Data mining; Electricity markets; Multidimensional forecasting; Neural networks; Time series

Indexed keywords

DATA MINING; FORECASTING; LINEAR NETWORKS; MULTILAYER NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SENSITIVITY ANALYSIS; TIME SERIES ANALYSIS;

ELECTRICITY MARKETS; MULTIDIMENSIONAL FORECASTING; SYSTEM IMBALANCE VOLUME;

ELECTRIC POWER SYSTEMS;

EID: 32144446774     PISSN: 08858950     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPWRS.2005.860924     Document Type: Article

References (32)

1. P. K. Dash, G. Ramakrishna, A. C. Liew, and S. Rahman, "Fuzzy neural networks for time-series forecasting of electric load," Proc. Inst. Elect. Eng., Gener., Transm., Distrib., vol. 142, no. 5, pp. 535-544, Sep. 1995.
2. D. W. Bunn, "Forecasting loads and prices in competitive power markets," Proc. IEEE, vol. 88, no. 2, pp. 163-169, Feb. 2000.
3. A. Sfetsos, "Short-term load forecasting with a hybrid clustering algorithm," in Proc. Inst. Elect. Eng., Gener., Transm., Distrib., vol. 150, May 2003, pp. 257-262.
4. B. Kermanshahi and H. Iwamiya, "Up to year 2020 load forecasting using neural nets," Int. J. Elect. Power Energy Syst., vol. 24, pp. 789-797, 2002.
5. J. Bastian, J. Zhu, V. Banunarayanan, and R. Mukerji, "Forecasting energy prices in a competitive market," Inst. Elect. Eng. Comput. Appl. Power, pp. 40-45, 1999.
6. J. C. Cuaresma, J. Hlouskova, S. Kossmeier, and M. Obersteiner, "Forecasting electricity spot-prices using linear univariate time-series models," Appl. Energy, vol. 77, pp. 87-106, 2004.
7. C. P. Rodriguez and G. J. Anders, "Energy price forecasting in the Ontario competitive power system market," IEEE Trans. Power Syst., vol. 19, no. 1, pp. 366-374, Feb. 2004.
8. X. Wang, N. Hatziargyriou, and L. H. Tsoulakas, "A new methodology for nodal forecasting in deregulated power systems," IEEE Power Eng. Rev., pp. 48-51, 2002.
9. F. J. Nogales, J. Contreras, A. J. Conejo, and R. Espinola, "Forecasting next-day electricity prices by time series models," IEEE Trans. Power Syst., vol. 17, no. 2, pp. 342-348, May 2002.
10. J. Contreras, R. Espinola, F. Nogales, and A. J. Conejo, "ARIMA models to predict next-day electricity prices," IEEE Trans. Power Syst., vol. 18, no. 3, pp. 1014-1020, Aug. 2003.
11. D. Pilipovic, "Energy risk: Valuing and managing energy derivatives," J. Energy Lit., vol. 4, p. 111, 1998.
12. P. Stephenson and M. Paun, "Electricity market trading," Power Eng. J., vol. 15, no. 6, pp. 277-288, Dec. 2001.
13. Office of Gas and Electricity Markets (OFGEM), "NGC System Operator Incentive Scheme from April 2004,", Dec. 2003.
14. R. S. Tsay, "Analysis of financial time series," in Wiley Series in Probability & Statistics. New York: Wiley, Dec. 21, 2001, p. 472.
15. Z. Vojinovic, K. Vojislav, and R. Seidel, "A data mining approach to financial time series modeling and forecasting," Int. J. Intell. Syst. Account., Fin., Manage., vol. 10, pp. 225-239, 2001.
16. C. Pete, C. Julian, K. Randy, and K. Thomas, "CRISP-DM 1.0 Step-By-Step Data Mining Guide,", 2000.
17. D. Pyle, Data Preparation for Data Mining. San Francisco, CA: Morgan Kaufmann, 1999.
18. L. A. Wehenkel, Automatic Learning Techniques in Power Systems. Norwell, MA: Kluwer, 1998.
19. M. P. Garcia, "Forecasting system imbalance volumes and analysis of unusual events in competitive electricity markets," Ph.D. dissertation, Univ. Manchester, Manchester, U.K., 2005.
20. C. Antunes and A. Oliveira, "Temporal data mining: An overview," presented at the 7th ACM SIGKDD Int. Conf. Knowledge Discovery Data Mining (KDD-2001), San Francisco, CA, 2001.
21. M. Gavrilov, D. Anguelov, P. Indyk, and R. Motwani, "Mining the stock market: Which measure is best?" presented at the Conf. Knowledge Discovery Data, Boston, MA, 2000.
22. (2006) Electronic Statistics Textbook. Statsoft, Tulsa, OK. [Online]. Available: http://www.statsoft.com/textbook/stathome.html
23. D. Peña, G. C. Tiao, and R. Tsay, "Basic concepts in univariate time series," in A Course in Time Series Analysis, Wiley series in Probability and Statistics. Probability and statistics, J. W. Sons, Ed. New York: Wiley-Interscience, 2000, p. 496.
24. J. B. Elsner and A. A. Tsonis, "Singular spectrum analysis: A new tool in time series analysis," in A New Tool in Time Series Analysis, J. B. Elsner, Ed. New York: Plenum, 1996.
25. N. Golyandina, V. Nekrutkin, and A. Zhigljavsky, Analysis of Time Series Structure. SSA and Related Techniques, 2001.
26. C. Alexander, Market Models: A Guide to Financial Data Analysis. New York: Wiley, 2001.
27. S. K. Kachigan, Multivariate Statistical Analysis: A Conceptual Introduction, 2nd ed. New York: Radius, 1991.
28. T. Kohonen, Self-Organizing Maps, 3rd ed., 2001.
29. T. Kolarik and G. Rudorfer, "Time series forecasting using neural networks," J. Time Series Neural Netw., pp. 86-94, 2004.
30. S.-H. C. a. S. H. Kim, "Data mining for financial prediction and trading: Application to single and multiple markets," Expert Syst. Appl., vol. 26, pp. 131-139, 2004.
31. Y. JingTao and T. C. Lim, "Guidelines for financial forecasting with neural networks," presented at the Int. Conf. Neural Information Processing, Shanghai, China, 2001.
32. H. Y. Yamin, S. Shahidehpour, and Z. Li, "Adaptive short-term electricity price forecasting using artificial neural networks in the restructured power markets," Elect. Power Energy Syst., vol. 26, pp. 571-581, 2004.