International Journal of Energy Engineering          
International Journal of Energy Engineering(IJEE)
ISSN:2225-6563(Print)
ISSN:2225-6571(Online)
Frequency: Yearly
Editor-in-Chief: Prof. Sri Bandyopadhyay(Australia)
Day-ahead Electricity Price Forecasting Using PSO -Based LLWNN Model
Full Paper(PDF, 214KB)
Abstract:
Price forecasting has become an important activity for market participants in electric power industry for developing their bidding strategies. The work presented in this paper makes use of particle swarm optimization based local linear wavelet neural networks (LLWNN) to find the Market Clearing Price (MCP) for a given period, with a certain confidence level. The results of the new method show significant improvement in the price forecasting process.
Keywords:Electricity Price, Forecasting, Wavelet Neural Network (WNN), Local Linear Wavelet Neural Network (LLWNN), Particle Swarm Optimization (PSO), Market Clearing Price (MCP), Weekly Mean Absolute Percentage Error (WMAPE)
Author: Prasanta kumar Pany1, Sakti Prasad Ghoshal2
1.Department of Electrical Engineering, DRIEMS,Cuttack, Odisha, India
2.Department of Electrical Engineering, National Institute of Technology, Durgapur, West Bengal, India
References:
  1. N. Amjady and M.Hemmati, “Energy price forecasting-problems and proposals for such predictions”. IEEE Power Energy Mag , 4(2), pp. 20-29, March 2006.
  2. M.Ranjbar, S.Soleymani, N.Sadati, and A.M.Ranjbar, “Electricity price forecasting using artificial neural network” . IEEE International Conference on Power Electronics, Drives and Energy System,pp.1-5 December 2006.
  3. Hsiao-Tien Pao, “Forecasting electricity market pricing using artificial neural network”. Energy Conversion and Management, vol.48,pp.907-912 Mar. 2007.
  4. Raquel Gareta, Luis M.Romeo, and Antonia Gil, “Forecasting electricity prices with neural networks”, Energy Conversion and Management,vol. 47,pp. 1770-1778 , August 2006.
  5. Paras Mandal, Tomonobu Senjyu, Naomitsu Urasaki, Toshihisa Funabashi, and Anurag K. Srivastrava, “Short-term price forecasting for competitive electricity market”, 38th North American Power Symposium,pp.137-141, Sept. 2006..
  6. J.P.S. Catalao, S.J.P.S. Mariano, V.M.F. Mendes, and L.A.F.M. Ferreira, “Short-term price forecasting in a competitive market, A neural network approach”, Electric Power System Research, vol.21, pp.1297-1304 ,August 2007.
  7. Nima Amjady, “Day-Ahead price forecasting of electricity markets by fuzzy neural networks”, IEEE Transaction on Power System, vol.21,pp. 887-896, May 2006.
  8. Ciwei Gao, Ettore Bomparb, Roberto Napoli, and Haozhou zhenz, “Price forecast in the competitive electricity market by support vector machine”, Physica A.vol.382,pp. 98-113, August 2007.
  9. S. Fan, C. Mao, and L. Chen, “Next-day electricity price forecasting using a hybrid network”, IEEE Generation Transmission & Distribution, vol.1, pp.176-182. Jan.2007.
  10. A.M. Gonzalez, A.M.S. Roque, and J. Garcia-Gonzalez, “Modeling and forecasting electricity price with input/output hidden Markov models”, IEEE Transactions on Power systems.vol. 20(1), pp. 13-24, Feb. 2005.
  11. J. Contreras, R. Espinola, F.J. Nogales, and A.J. Conejo, “ARIMA models to predict next day electricity prices”, IEEE Transactions on Power systems, vol.18(3),pp.1014-1020, Aug. 2003.
  12. F.J. Nogales, J. Contreras, A.J. Conejo, and R. Espinola, “Forecasting next day electricity prices by time series models”, IEEE Transactions on Power Systems, vol. 17(2), pp.342-348, May 2002.
  13. R.C.Garcia, J. Contreras, M. van Akkeren, and J.B.C. Garcia, A GARCH forecasting model to predict day-ahead electricity prices. IEEE Trans. Power System, May 2005; 20(2):867-874.
  14. Q. Zhang and A. Benveniste, “Wavelet networks”, IEEE Trans. Power Syst.,vol. 3(6), pp.889-898, Nov. 1992.
  15. Y. Chen, J. Dong, Bo Yang and Y. Zhang, “A Local Linear Wavelet Neural Network”, IEEE Proceeding of the 5th World Congress on Intelligent Control and Automation, pp.1954-1957, June 2004.
  16. Kennedy et al, “Particle Swarm Optimization”, Proc. Of IEEE International Conference on Neural Networks, vol.4,pp.1942-1948,1995.
  17. 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 Trans. Power Syst, vol.20(2),pp.1035-1042, May 2005.
  18. S.K. Aggarwal, Lalit Mohan, and Ashwani Kumar, “Electricity price forecasting in Ontario Electricity Market Using Wavelet Transform in Artificial Neural network based model”, I J.of Control, Automation, and Systems, vol. 6(5), 639-650, Oct. 2008.
  19. G.J. Anders, and C. Rodriguez, “Energy price forecasting and Bidding Strategy in the Ontario Power System Market”, Power Tech. Conference, June 2005.
  20. C.P. Rodriguez, and G.J.Anders, “Energy Price Forecasting in the Ontario Competitive Power System Market”, IEEE Trans. Power Syst. ,vol.19(1), pp.366-374, Feb. 2004.