Research on Short Term Load Forecasting of Power System

Abstract:

The short term load forecast of power system is one of the important tasks of power dispatch and service department, whose accuracy has a close relation with dispatch operation, production plan and quality of power supply. Artificial neural network was introduced into forecasting of short term load. Aiming at the drawback in classical BP artificial networks and combining with differential evolution algorithms, this paper puts forwards the prediction model based on real number coded DE-BP artificial networks. Experimental result show this model has high prediction accuracy and can be used into real project.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 1666-1670
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.1666
• Online since: January 2012
• Authors: Li Zhong Wang, Tie Nan Liu, Hui Zhao, Hong Bo Liu
• Keywords: Forecast, Model, Short Term Load

References

[1] Bashir Z, E Haw, Short term load forecasting by using wavelet neural network, Conference on electrical and computer engineering, Halifax, Canada, pp.192-206, (2006).

[2] Fortuna L, Grazianis, Soft sensors for product quality monitoring in debutanizer distillation columns, Control Engineering Practice, vol. 13, pp.499-508, Aug (2005).

DOI: 10.1016/j.conengprac.2004.04.013

[3] Ben F, Amamou R, Surface routhness prediction based upon experimental design and neural network models, IEEE Internal Conference on Systems, Washington, Dec. 2006, pp.752-756.

DOI: 10.1109/icsmc.2002.1176341

[4] DANGJianW, Neural network technology and its application ， Beijing: China Railway Press, (2000).

[5] Enneth P, Rainer M, Jouni A. L, Differential evolution: A practical approach to global optimization (Natural Computing Series), Springer, (2006).

[6] Ferbec K, Haeperic Y, An approach to customers daily load profile determination, IEEE power engineering society summer meeting, Chicago, USA: Aug. 2007, pp.587-596.

[7] SHI Dong-hui, Outlier data mining application in power load forecasting, Computer Engineering and Applications, vol. 46, No21, Jul. 2010, pp.213-215.

[8] GUO Hua , YANG Ding-yuan, The method and characteristic of load forecast for distribution network layout, Ningxia Electric Power, NoS1, Dec. 2004, pp.101-102.

[9] LI Hui, Application of combined gray model to power load data pretreatment, Journal of Beijing Information Science & Technology University, No2, Jun. 2010, pp.73-77.

[10] MAO Li-fan, YAO Jian-gang, JIN Yong-shun，etc, Theoretical Study of Combination Model for Medium and Long Term Load Forecasting, Proceedings of the CSEE, No16, Jun. 2010, pp.55-61.