Short term load forecasting by using neural network structure

2009 6th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2009

Volumn 1, Issue , 2009, Pages 240-243

  Mirhosseini, M ^a   Marzband, M ^b,c   Oloomi, M ^d  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b NATIONAL PETROCHEMICAL COMPANY   (Iran)

^c Borzouyeh Petrochemical Company   (Iran)

^d Khorasan Regional Electric Company   (Iran)

Author keywords

Daily load; Load forecasting; Neural network; Short term load

Indexed keywords

DAILY LOAD; DATA BASE; ELECTRICAL INDUSTRY; ELECTRICITY MARKET; LOAD FORECASTING; MATLAB ENVIRONMENT; MAXIMUM ERROR; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; NEURAL NETWORK STRUCTURES; POWER SYSTEMS; SHORT TERM LOAD; SHORT TERM LOAD FORECASTING; TIME-ACCURATE; TIME-CONSUMING TASKS; VISUAL BASIC;

INFORMATION TECHNOLOGY; MATLAB; NEURAL NETWORKS; SPREADSHEETS;

ELECTRIC LOAD FORECASTING;

EID: 70350046930     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ECTICON.2009.5137001     Document Type: Conference Paper

References (12)

1. K. Kim, H. S. Youn, and Y. C. Kang, "Short-term load forecasting for special days in anomalous load conditions using neural networks and fuzzy inference method," IEEE Trans. Power Syst., vol. 15, no. 2, pp. 559-565, 2000.
2. A. D. Papalexopoulos and T. C. Hesterberg, "A regression-based approach to short-term load forecasting," IEEE Trans. Power Syst., vol. 5, no. 4, pp. 1535-1550, 1990.
3. T. Haida and S. Muto, "Regression based peak load forecasting using a transformation technique," IEEE Trans. Power Syst., vol. 9, no. 4, pp. 1788-1794, 1994.
4. S. Rahman and O. Hazim, "A generalized knowledge-based short term load-forecasting technique", IEEE Trans. Power Syst., vol. 8, no. 2, pp. 508-514, 1993.
5. S. J. Huang and K. R. Shih, "Short-term load forecasting via ARMA model identification including nongaussian process considerations", IEEE Trans. Power Syst., vol. 18, no. 2, pp. 673-679, 2003.
6. H.Wu and C. Lu, "A data mining approach for spatial modeling in small area load forecast," IEEE Trans. Power Syst., vol. 17, no. 2, pp. 516-521, 2003.
7. H. S. Hippert, C. E. Pedreira, and R. C. Souza, "Neural networks for short-term load forecasting: A review and evaluation," IEEE Trans.Power Syst., vol. 16, no. 1, pp. 44-55, 2001.
8. S. Rahman and G. Shrestha, "A priory vector based technique for load forecasting," IEEE Trans. Power Syst., vol. 6, no. 4, pp. 1459-1464, 1993.
9. S. Rahman and R. Bhatnagar, "An expert system based algorithm for short term load forecast," IEEE Trans. Power Syst., vol. 3, no. 2, pp. 392-399, 1988.
10. D. Srinivasan, C. S. Chang, and A. C. Liew, "Demand forecasting using fuzzy neural computation, with special emphasis on weekend and public holiday forecasting," IEEE Trans. Power Syst., vol. 10, no. 2, pp. 1897-1903, 1995.
11. R. Lamedica, A. Prudenzi, M. Sforna, M. Caciotta, and V. O. Cencellli, "A neural network based technique for short-term forecasting of anomalous load periods," IEEE Trans. Power Syst., vol. 11, no. 4, pp. 1749-1750, 1996.
12. T. Senjyu, H. Takara, K. Uezato, and T. Funabashi, "One-hour-ahead load forecasting using neural network," IEEE Trans. Power Syst., vol. 17, no. 1, pp. 113-118, 2002.