Study on Wind Speed Forecasting Based on STC and BP Neural Network

Abstract:

Accurate wind speed forecasting of wind farm is of great significance in economic security and stability of the grid. In order to improve the prediction accuracy, the paper first proposed a spatio-temporal correlation predictor method. Based on physical characteristics of wind speed evolution, the method looked for the wind speed and direction information at sites close to the target prediction site, and established STCP model to forecast. And then we established the BP neural network to finish multi-step forecast with wind speed time series of target forecast site .Last, two methods were combined to form STCP-BP method. Simulation tests are conducted with operation data from certain wind farm group in China and results show that STCP-BP method can effectively improve the prediction accuracy compared with BP model.

• Periodical: Advanced Materials Research (Volumes 724-725)
• Pages: 623-629
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.724-725.623
• Online since: August 2013
• Authors: Xing Jie Liu, Wen Shu Zheng, Tian Yun Cen
• Keywords: BP Neural Network (BPNN), Spatio-Temporal Correlation, Wind Farm, Wind Speed Forecasting

References

[1] Ming Yin, Xubo GE, Chengshan Wang. Analysis of Issues about China's Large-scale Wind Power Development [J].Electric Power.2010.43(3):59-63.

[2] Ruiye Liu, Lei Huang.Wind Power Forecasting Based on Dynamic Neural Networks [J]. Automation of Electric Power Systems. 2012.36(11).

[3] Jinwei Fu, Jin Ma，Yuxiao Zhou. Review on Wind Power Prediction Methods[J]. East China Electric Power. 2012.40(5):0889-0892.

[4] Difu Pan, Hui Liu, Yanfei Li. Optimization Algorithm of Short-term Multi-step Wind Speed Forecast [J]. Proceedings of the CSEE. 2008,28(26):87-91.

[5] Xingkai Gu, Gaofeng Fan, Xiaorong Wang， Haixiang Zhao，Huizhu Dai. Summarization of Wind Power Prediction Technology [J]. Power System Technology. 2007,31(Sup 2):335-338.

[6] Gaofeng Fan, Weisheng Wang, Chun Liu, Huizhu Dai. Wind Power Prediction Based on Artificial Neural Network[J]. Proceedings of the CSEE. 2008,28(34):118-123.

[7] MingDing, Lijun Zhang, Yichun Wu. Wind Speed Forecast Model for Wind Farms Based on Time Series Analysis [J]. Electric Power Automation Equipment. 2005,25(8):32-34.

[8] Difu Pan, Hui Liu, Yanfei Li. A Wind Speed Forecasting Optimization Model for Wind Farms Based on Time Series Analysis and Kalman Filter Algorithm [J]. Power System Technology. 2008, 32(7): 82-86.

[9] Shuang Gao, Lei Dong, Yang Gao, Xiaozhong Liao. Mid-long Term Wind Speed Prediction Based on Rough Set Theory [J]. Proceedings of the CSEE. 2012.32(1):32-37.

[10] Shao Wang, Jiangping Yang, Fengbing Li, Tinglei Liu. Short-term Wind Speed Forecasting Based on EMD and ANN J]. Power System Protection and Control. 2012.40(10):6-11.

[11] Xiuyuan Yang, Yang Xiao, Shuyong Chen. Wind Speed and Generated Power Forecasting in Wind Farm[J]. Proceedings of the CSEE. 2005, 25(11):1-5.

[12] Wenliang Li,Zhinong Wei,Guoqiang Sun, Zheng Wan,Wei Miao.Multi-interval Wind Speed Forecast Model Based on Improved Spatial Correlation and RBF Neural Network [J].Electric Power Automation Equipment. 2009, 29(6):89-91.

[13] T.G. Barbounis, J.B. Theocharis, Locally recurrent neural networks optimal filtering algorithms: application to wind speed prediction using spatial correlation, in: Proc. IEEE International Joint Conf. Neural Networks, 2005, p.2711–2716.

DOI: 10.1109/ijcnn.2005.1556353

[14] I.G. Damousis, M.C. Alexiadis, J.B. Theocharis, P.S. Dokopoulos, A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation, IEEE Trans. Energy Conversion 19 (2) (2004) 352–361.

DOI: 10.1109/tec.2003.821865

[15] Rong Zhi, Guolin Feng, Zhiqiang Gong, Lei Zhou. Temporal and Spatial Correlation Analysis of Global Temperature Data Based on the Correlation Matrix Theory [J].Acta Meteorologica Sinica.2010.68(4):501-513.

[16] L. Landberg, Short-term prediction of the power production from wind farms. Journal of Wind Engineering and Industrial Aerodynamics, vol. 80, pp.207-220, 1999.

DOI: 10.1016/s0167-6105(98)00192-5

[17] Hongyan Zhang, Zheng Geng. Novel interpretation for Levenberg-Marquardt Algorithm. Computer engineering and applications. 2009.45(19).5-8.

[18] Zengqiang Mi, Xingjie Liu, Yanqing Zhang, Qixun Yang. Direct Mulyi-Step Forecasting of Short-Term Wind Speed Based on Chaos Analysis and Neural Network [J]. Acta Energiae Solaris Sinica. 2011.32(6):901-905.

DOI: 10.1109/supergen.2009.5348114

[19] Defeng Zhang.The Application of MATLAB Neural Network Design [M].Beijing: Machinery Industry Press. 2011.12.

[20] Haikun Wei.The Theory and Method of Neural Network Structure Design [M].Beijing: National Defence Industry Press.2005.2.

[21] M.C. Alexiadis, P.S. Dokopoulos, H.S. Sahsamanoglou, Wind speed and power forecasting based on spatial correlation models, IEEE Trans. Energy Conversion 14 (1999) 836–842.

DOI: 10.1109/60.790962

[22] Guoqiang Zhang, Boming Zhang. Wind Speed and Wind Turbine Output Forecast Based on Combination Method [J]. Automation of Electric Power Systems.2009, 33(18):92-96.