A Study of Photovoltaic Power Prediction

Abstract:

Solar photovoltaic power generation as an inexhaustible, inexhaustible clean energy has become the focus of future energy development. Along with photovoltaic power generation incorporated into the power grid, in order to make power generation plan reasonably, ensure the stable operation of power system, need to forecast the photovoltaic power output. In this paper solar photovoltaic power generation forecasting methods are analyzed and summarized. According to the application of solar photovoltaic power generation and demand, mainly on photovoltaic power generation system power prediction research method has carried on the comprehensive elaboration, hoping for the researches play an important role in promoting and advancing the development of solar photovoltaic prediction methods.

• Periodical: Applied Mechanics and Materials (Volume 733)
• Pages: 203-206
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.733.203
• Online since: February 2015
• Authors: Yan Long Li, Jing Xu, Chong Yuan
• Keywords: Forecasting Methods, Photovoltaic Power Generation, Power Prediction

References

[1] J. Xu, Z.H. Chen, J. Tang, et al: Solar photovoltaic power generation forecasting website system designs and evaluates, J. Journal of Hydroelectric Energy Science, Vol. 29 (2011) No. 12, pp.193-195.

[2] Y. Deng, S.J. Hu, Y. F. Meng, H. H. Xu: Methods of photovoltaic power generation system power prediction, J. Electric Manufacturing, (2013) No. 6, pp.50-53.

[3] V. Vapnik: An overview of statistical learning going, J. IEEE Trans on Neural Networks, Vol. 10 (1999), No. 5, p . 988-999.

DOI: 10.1109/72.788640

[4] J, Lu, H. Q. Zhai, C. Liu, et al: Photovoltaic power prediction statistical method research, J. Journal of East China Power, Vol. 38(2010) No. 4, pp.563-567.

[5] P. Bracale Caramia, G. Carpinelli, et al: A Bayesian method for short-term probabilistic forecasting of photovoltaic generation in smart grid operation and control, J. Journal of Energy, (2013) No. 6. pp.733-747.

DOI: 10.3390/en6020733

[6] W.L. Hu, H. W. Wang: Support vector machine prediction model based on Bayesian criteria, J. Journal of Beijing University of aeronautics and astronautics, Vol. 4 (2010), No. 4, pp.486-489.

[7] R. Li, G. M. Li : Based on support vector machine regression PV output forecast, J. Journal of China power, Vol. 9(2008), No. 2, pp.74-78.

[8] Li Yingzi, Luan, Ru Niu Jincang. The Forecast of the power generation for the grid - connected photovoltaic system -based on grey model and Markov Chain, C. 3rd IEEE Conference on Industrial Electronics and Applications. Singapore, 2008: pp.1729-1733.

DOI: 10.1109/iciea.2010.5517032

[9] M.Q. He, C. Cheng, Z. H . Chen, et al: Solar photovoltaic power generation forecasting effect evaluates, J. Water and electricity energy science, Vol. 29 (2011), No. 12, pp.196-199.