Modeling and forecasting of energy prices using non-stationary Markov models versus stationary hybrid models including a survey of all methods

2007 IEEE Canada Electrical Power Conference, EPC 2007

Volumn , Issue , 2007, Pages 429-434

  Haghi, Hamed Valizadeh ^a   Tafreshi, S M Moghaddas ^a  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Hidden Markov models; Non stationary time series; Price forecasting; Price models; Stationary time series; Wavelet transform

Indexed keywords

ELECTRIC LOAD FORECASTING; ELECTRIC POWER SUPPLIES TO APPARATUS; ENERGY UTILIZATION; FORECASTING; MARKOV PROCESSES; SURVEYS; TECHNOLOGICAL FORECASTING; TIME SERIES ANALYSIS; WAVELET TRANSFORMS;

BIDDING STRATEGIES; COMPETITIVE ELECTRICITY MARKETS; ELECTRICAL POWER; ENERGY PRICING; HYBRID MODELLING; MARKOV MODELLING; MODELING AND FORECASTING; NON-STATIONARY; NON-STATIONARY TIME SERIES; PRICE FORECASTING; PRICE MODELS; STATIONARY TIME SERIES; TIME SERIES MODELING; WAVELET TRANSFORM;

HIDDEN MARKOV MODELS;

EID: 49249125007     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EPC.2007.4520370     Document Type: Conference Paper

References (14)

1. J. Bastian, J. Zhu, V. Banunarayanan, and R. Mukerji, "Forecasting energy prices in a competitive market," IEEE Computer Applications in Power, vol. 12, no. 3, pp. 40-45, July 1999.
2. G. Li, C. Liu, J. Lawarree, M. Gallanti, A. Yenturini, "State-of-the-art of electricity price forecasting," IEEE, 2005.
3. A. M. Gonzalez, A. M. San Roque, and J. Garcia-Gonzalez, "Modeling and forecasting electricity prices With input/Output hidden Markov models," IEEE. Transactions on Power Systems, vol. 20, no.1, pp. 13-24, Feb. 2005.
4. A. J. Conejo, M. A. Plazas, R. Espinola, and A. B. Molina, "Day-ahead electricity price forecasting using the Wavelet transform, and ARIMA models," IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 1035-1042, May .2005.
5. N. Amjady, and M. Hemmati, "Energy price forecasting, problems and proposals for Such predictions,"'IEEE Power and Energy Magazine, pp. 20-29, March/April 2006.
6. B. R. Szkuta, L. A. Sanavria and T. S. Dillon, "Electricity Price ShortTerm Forecasting Using Artificial Neural Networks," IEEE Transactions on Power Systems, Vol. 14, No. 3, pp. 851-857, Aug. 1999.
7. Y.-Y. Hong, and C.-F. Lee, "A neuro-fuzzy price forecasting approach in deregulated electricity markets," Electric Power Systems Research, no. 73, pp. 151-157, 2005.
8. J. H. Zhao, Z. Y. Dong, X. Li, and K. P. Wong, "A general method for electricity market price spike analysis," IEEE, 0-7803-9156, 2005.
9. P. Kosater, and K. Mosler, "Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power pnces," Applied Energy, no. 83, pp. 943-958, 2006.
10. W. Yu, G. "B. Sheble, "Modeling electricity markets with hidden Markov model," Electric Power Systems Research, no. 76, pp. 445-451, 2006.
11. OMEL Market "Prices, retrieved November 19, 2006. http://www.omel.es
12. A. Papoulis, Probability, Random Variables, and Stochastic Processes. McGraw-Hill, 2002.
13. J. D. Hamilton, Time Series Analysis, Princeton University Press, 1994.
14. The Math Works, MATLAB. (2007). Available online: http://www.mathworks: com