Short-term daily peak load forecasting using fast learning neural network

International Conference on Intelligent Systems Design and Applications, ISDA

Volumn , Issue , 2011, Pages 843-848

  Khan, Gul Muhammad ^a   Khan, Shahid ^a   Ullah, Fahad ^a  

^a UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Pakistan)

Author keywords

Artificial Neural Networks; Genetic Programming; Neuro evolution; Short Term Load Forecasting

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CARTESIANS; DAILY PEAK LOAD; ELECTRIC POWER; ELECTRIC POWER SUPPLY; FAST LEARNING; LOAD FORECASTING; NEURO-EVOLUTION; PEAK LOAD; PEAK LOAD FORECASTING; SHORT TERM LOAD FORECASTING;

GENETIC ALGORITHMS; GENETIC PROGRAMMING; INTELLIGENT SYSTEMS; NEURAL NETWORKS; SYSTEMS ANALYSIS; TOPOLOGY;

ELECTRIC LOAD FORECASTING;

EID: 84857516869     PISSN: 21647143     EISSN: 21647151     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2011.6121762     Document Type: Conference Paper

References (23)

1. S. Abbas and A. M. Electric load forecasting using support vector machines optimzed by genetic algorithm. In Proc. CIMCA '05, pages 395-399, 2006.
2. A. J. Al-Shareef, E. A. Mohamed, and E. Al-Judaibi. One hour ahead load forecasting using artificial neural network for the western area of saudi arabia. 2008.
3. N. Amjady and F. Keynia. Mid-term load forecasting of power systems by a new prediction method. Energy Conversion and Management, 49(10):2678-2687, 2008.
4. E. Barakat, M. Qayyum, M. Hamed, and S. A. Al-Rashed. Short-term peak demand forecasting in fast developing utility with inherent dynamic load characteristics. IEEE Transactions on Power Systems, 5:813-824, 1990. (Pubitemid 20739220)
5. E. E. El-Attar, J. Goulemas, and Q. Wu. Forecasting electric daily peak load based on local prediction. In Power and Energy Society General Meeting, pages 1-6, 2009.
6. V. H. Ferreira and A. P. Alves da Silva. Toward estimating autonomous neural network-based electric load forecasters. IEEE Trans. Power Systems, 22(4):1554-1562, 2007.
7. M. Ghomi, M. Goodarzi, and M. Goodarzi. Peak load forecasting of electric utilities for west province of iran by using neural network without weather information. In Proc. UKSIM '10, pages 28-32, 2010.
8. F. Gomez, J. Schmidhuber, and R. Miikkulainen. Accelerated neural evolution through cooperatively coevolved synapses. J. Mach. Learn. Res., 9:937-965, 2008.
9. M. M. Khan, G. M. Khan, and J. F. Miller. Evolution of neural networks using cartesian genetic programming. In IEEE CEC'10, pages 1-8, 2010.
10. A. Koushki, M. maralloo, B. Hashemitabar, and C. Lucas. Load forecasting with the aid of neuro-fuzzy modeling. In Proceeding of Seventh International Conference on CSIT, 2009.
11. K. Liu, S. Subbarayan, R. R. Shoults, M. T. Manry, C. Kwan, F. I. Lewis, and J. Naccarino. Comparison of very short-term load forecasting techniques. IEEE Transactions on Power Systems, 11(2):877-882, 1996. (Pubitemid 126781230)
12. H. Mao, X.-J. Zeng, G. Leng, Y. Zhai, and J. A. Keane. Short and mid-term load forecasting using a bilevel optimization model. IEEE Transactions on Power Systems, 24(2):1080-1090, 2009.
13. T. Matsui, T. Iizaka, and Y. Fukuyama. Peak load forecasting using analyzable structured neural network. IEEE Power Engineering Society Winter Meeting, 2:405, 2002.
14. J. R. Mcdonald, K. L. Lo, and P. M. Sherwood. Application of short-term adaptive forecasting techniques in energy management for the control of electric load. Transactions of the Institute of Measurement and Control, 11:79-91, 1989.
15. J. F. Miller and P. Thomson. Cartesian genetic programming. In Proc. of the 3rd European Conf. on Genetic Programming, volume 1802, pages 121-132, 2000.
16. D. Moriarty. Symbiotic Evolution of Neural Networks in Sequential Decision Tasks. PhD thesis, University of Texas at Austin, 1997.
17. D. Ortiz-Arroyo, M. K. Skov, and Q. Huynh. Accurate electricity load forecasting with artificial neural networks. In Proc. CIMCA '05, pages 94-99, 2005.
18. T. Peng, N. Hubele, and G. Karady. Advancement in the application of neural networks for short-term load forecasting. IEEE Transactions on Power Systems, 7:250-257, 1992.
19. P. Qingle and Z. Min. Very short-term load forecasting based on neural network and rough set. In Proc.ICICTA '10, pages 1132-1135, 2010.
20. K. O. Stanley and R. Miikkulainen. Evolving neural network through augmenting topologies. Evolutionary Computation, 10(2):99-127, 2002.
21. X. Tao, H. Renmu, W. Peng, and D. Xu. Input dimension reduction for load forecasting based on support vector machine. In IEEE DRPT Conference, pages 510-513, 2004.
22. H.-T. Yang, C.-M. Huang, and C.-L. Huang. Identification of armax model for short term load forecasting: an evolutionary programming approach. IEEE Transactions on Power Systems, 11:403-408, 1996. (Pubitemid 126781172)
23. X. Yao. Evolving artificial neural networks. In Proceedings of the IEEE, volume 87(9), pages 1423-1447, 1999. (Pubitemid 30503424)