Short-term load forecasting using support vector machine with SCE-UA algorithm

Proceedings - Third International Conference on Natural Computation, ICNC 2007

Volumn 1, Issue , 2007, Pages 290-294

  Li, Gang ^a   Cheng, Chun Tian ^a   Lin, Jian Yi ^a   Zeng, Yun ^a  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

SCE UA algorithm; Short term load forecasting; Similar day; SVM

Indexed keywords

ALGORITHMS; DEREGULATION; MATHEMATICAL MODELS; PRIVATIZATION; SUPPORT VECTOR MACHINES;

POWER SYSTEM PLANNING; SCE-UA ALGORITHM; SHORT-TERM LOAD FORECASTING; SIMILAR DAY;

ELECTRIC LOAD FORECASTING;

EID: 38049035603     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNC.2007.660     Document Type: Conference Paper

References (18)

1. Amjady, N., "Short-term hourly load forecasting using time-series modeling with peak load estimation capability," IEEE Transactions on Power Systems, vol. 16, pp. 498 505, 2001.
2. Shyh-Jier Huang and Kuang-Rong Shih, "Short-term load forecasting via ARMA model identification including nonGaussian process considerations, " IEEE Transactions on Power Systems, vol. 18, pp. 673 - 679, 2003.
3. H.M. Al-Hamadi and SA. Soliman, "Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model," Electric Power Systems Research, vol. 68, pp. 47-59, 2004.
4. Kwang-Ho Kim, Jong-Keun Park, Kab-Ju Hwang and Sung-Hak Kim, "Implementation of hybrid short-term load forecasting system using artificial neural networks and fuzzy expert-systems," IEEE Transactions on Power Systems, vol. 10, pp. 1534-1539, 1995.
5. B. Satish, K. S. Swamp, S. Srinivas, and A. H. Rao, "Effect of temperature on short term load forecasting using an integrated ANN," Electric Power Systems Research, vol. 72, pp. 95-101, 2004.
6. Dipti Srinivasan, "Evolving artificial neural networks for short term load forecasting," Neurocomputing, vol. 23, pp. 265-276, 1998.
7. Vapnik V. N., the Nature of Statistical Learning Theory: New York: Springer-Verlag, 1995.
8. Ying-chun Guo, Dong-xiao Niu, Yan-xu Chen, "Supprot Vector Mahicne Model in Electricity Load Forecasting," Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, Dalian, 2006.
9. Xun-ming Li, Deng-cai Gong, Lin-feng Li, and Changyin Sun, "Next Day Load Forecasting Using SVM," Lecture notes in computer science, pp. 634-639, 2005.
10. Ming-guang Zhang, "Short-term load forecasting based on support vector machines regression," Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, 2005.
11. Ping-Feng Pai and Wei-Chiang Hong, "Forecasting regional electricity load based on recurrent support vector machines with genetic algorithms," Electric Power Systems Research, vol. 74, pp. 417-425, 2005.
12. F.P. Ping and C.H. Wei, "Support vector machines with simulated annealing algorithms in electricity load forecasting," Energy Conversion and Management, vol. 46, pp. 2669-2688, 2005.
13. Changyin Sun and Dengcai Gong, "Support Vector Machines with PSO Algorithm for Short-Term Load Forecasting," Networking, ICNSC '06. Proceedings of the 2006 IEEE International Conference on, 2006.
14. Duan Q.Y., S. Sorooshian, and V.K. Gupta, "Effective and efficient global optimization for conceptual rainfall-runoff models," Water Resources Research, vol. 28, pp. 1015-1031, 1992.
15. Duan Q. Y., V. K. Gupta, and S. Sorooshian, "Shuffled complex evolution approach for effective and efficient minimization," Journal of Optimization Theory and Applications, vol. 76, pp. 501-521, 1993.
16. Duan Q.Y., S. Sorooshian, and V.K. Gupta, "Optimal use of the SCE-UA global optimization method for calibrating watershed models," Journal of Hydrology, vol. 158, pp. 265-284, 1994.
17. Yu, X.Y., S.Y. Liong, and V. Babovic, EC-SVM approach for real-time hydrologic forecasting, Journal of Hydroinformatics, 6(3), 209-233.
18. Chongqing Kang, Xu Cheng, Qing Xia, Yonghao Huang and Feng Gao, "Novel approach considering load-relative factors in short-term load forecasting," Electric Power Systems Research, vol.70, pp. 99-107, 2004.