Abstract
Wind power prediction is important to wind power system operation with a large amount of wind power integration. Effective prediction for wind power can reduce the difficulty of grid dispatching. In this paper an advanced neural network model was proposed to predict the short-term output power of a single wind turbine in a wind farm. According to the relevant wind speed, wind direction, temperature, output power and other data obtained from the wind farm, the model was established to predict the output wind power ahead of 10 min and 1 h. The simulation results showed that the proposed advanced BP neural network model had a higher prediction accuracy comparing to the existing BP neural network model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alexiadis M, Dokopoulos P, Sahsamanoglou H et al (1998) Short term forecasting of wind speed and related electrical power. Sol Energ 63(1):61–68
Campbell PRJ (2007) Short-term wind energy forecasting. Can Electr Power Conf 15(6):28–30
Kitajima T, Yasuno T (2010) Output prediction of wind power generation system using complex-valued neural network. SICE Annu Conf 50(33):18–21
Huang JH, Peng H (2009) Study of wind power short-term prediction of wind farm based on neural network. Electricity Electrotechnics 9(15):57–60
Peng HW, Liu FR, Yang XF (2009) Study of short-term wind power prediction based on artificial neural networks. East Chin Electric Power 37(11):1918–1921
Pinson P, Kariniotakis GN (2003) Wind power forecasting using fuzzy neural networks enhanced with on-line prediction risk assessment. IEEE Bologna PowerTech Conf 16(5):23–26
Fan GF, Wang WS, Liu C, Dai HZ (2008) Wind power prediction based on artificial neural network. Proc CSEE 28(34):118–123
Fu R, Wang WQ, He QX (2009) The forecasting of wind speed in wind farm based on the meter cal factors with BP neural network. Renew Energy Res 27(5):86–89
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this paper
Cite this paper
Lu, J., Yang, R., Zhang, C. (2013). Study of Short-Term Wind Power Prediction Based on Advanced BP Neural Network Model. In: Du, W. (eds) Informatics and Management Science IV. Lecture Notes in Electrical Engineering, vol 207. Springer, London. https://doi.org/10.1007/978-1-4471-4793-0_20
Download citation
DOI: https://doi.org/10.1007/978-1-4471-4793-0_20
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4792-3
Online ISBN: 978-1-4471-4793-0
eBook Packages: EngineeringEngineering (R0)