短期风速时间序列混沌特性分析及预测

田中大; 李树江; 王艳红; 高宪文

doi:10.7498/aps.64.030506

摘要

针对短期风速时间序列的预测问题进行了研究. 首先通过0-1混沌测试法确定短期风速时间序列具有混沌特性. 采用相空间重构技术, 利用C-C算法确定延迟时间, G-P 算法确定嵌入维数. 然后提出一种参数在线修正的最小二乘支持向量机预测模型, 采用改进的粒子群算法进行预测模型中参数的优化. 最后通过仿真对比实验表明提出的预测方法在预测精度、预测误差、预测效果方面都要优于其他常见的预测方法, 证明该预测方法是有效的.

关键词:

短期风速 /
时间序列 /
混沌 /
预测

Abstract

A short-term wind speed time series prediction is studied. First, 0-1 test method for chaos is used to identify the short-term wind speed time series that has chaotic characteristics. Through phase space reconstruction, the delay time is determined by using C-C algorithm; and the embedding dimension is determined by using G-P algorithm. Then a least square support vector machine with parameters online modified is proposed, so that an improved particle swarm optimization algorithm may be used for the prediction of parameters optimization. Simulation experiment shows that the present method for its prediction accuracy, prediction error, and prediction effect is better than other prediction methods. Thus the proposed prediction method is effective, and feasible.

Keywords:

作者及机构信息

1.
沈阳工业大学信息科学与工程学院, 沈阳 110870;

2.
东北大学信息科学与工程学院, 沈阳 110819

基金项目: 国家自然科学基金重点项目(批准号: 61034005)资助的课题.

Authors and contacts

1.
College of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China;

2.
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China

Funds: Project supported by the Key Program of the National Natural Science Foundation of China (Grant No. 61034005).

参考文献

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施引文献

[1]	Xiu C B, Liu X T, Zhang X, Yu T T 2013 Power System Protection and Control 41 14 (in Chinese) [修春波, 刘新婷, 张欣, 于婷婷 2013 电力系统保护与控制 41 14]
[2]	Yang X Y, Sun B J, Zhang X F, Li L X 2012 Proc. the CSEE 32 35 (in Chinese) [杨锡运, 孙宝君, 张新房, 李利霞 2012 中国电机工程学报 32 35]
[3]	Ma L, Benoudjit N 2011 Appl. Energ. 88 2463
[4]	Ma L, Luan S Y, Jiang C W, Liu H L, Zhang Y 2009 Renew. Sustain. Energy Rev. 13 915
[5]	Pelikán E, Eben K, Resler J, Juru P, Krc P, Brabec M, Brabec T, Musilek P 2010 9th Conference on Environment and Electrical Engineering (Piscataway, NJ: IEEE) p45
[6]	Cuo L, Zhang Y X, Wang Q C 2013 J. Climate 26 85
[7]	Erdem E, Shi J 2011 Appl. Energ. 88 1405
[8]	Jiang J L, Lin G M 2008 Control Theory Appl. 25 374 (in Chinese) [蒋金良, 林广明 2008 控制理论与应用 25 374]
[9]	Liu H, Tian H Q, Li Y F 2012 Appl. Energ. 98 415
[10]	Li H J, Liu Y N, Wei Z N, Li X L, Cheung K W, Sun Y H, Sun G Q 2013 Electr. Power Autom. Equip. 33 28 (in Chinese) [李彗杰, 刘亚男, 卫志农, 李晓露, Kwok W Cheung, 孙永辉, 孙国强 2013 电力自动化设备 33 28]
[11]	Wang Y, Wu D L, Guo C X, Wu Q H, Qian W Z, Yang J 2010 IEEE PES General Meeting (Piscataway, NJ: IEEE) p1
[12]	Li X, Wang X, Zheng Y H, Li L X, Zhou L D, Sheng X K 2014 International Conference on Renewable Energy and Environmental Technology (Zurich-Durnten: Trans Tech) p1825
[13]	Zeng J, Zhang H 2011 Acta Energiae Solaris Sin. 32 296 (in Chinese) [曾杰, 张华 2011 太阳能学报 32 296]
[14]	Louka P, Galanis G, Siebert N, Kariniotakis G, Katsafados P, Pytharoulis I, Kallos G 2008 J. Wind Eng. Ind. Aerodyn. 96 2348
[15]	Liu J B, Ding T 2012 Acta Energiae Solaris Sin. 33 1131 (in Chinese) [刘进宝, 丁涛 2012 太阳能学报 33 1131]
[16]	Fourati F, Chtourou M 2007 Simul. Model. Pract. Theory 15 1016
[17]	Xiao H F, Ding T 2011 Proceedings of the 2011 International Conference on Informatics, Cybernetics,Computer Engineering (Heidelberg: Springer) p479
[18]	Soman S S, Zareipour H, Malik O, Mandal P 2010 North American Power Symposium 2010 (Piscataway, NJ: IEEE) p1
[19]	Sheng Z 2012 Acta Phys. Sin. 61 219401 (in Chinese) [盛峥 2012 61 219401]
[20]	Tahat A, Marti J, Khwaldeh A, Tahat K 2014 Chin. Phys. 23 046101
[21]	Li H C, Zhao J S 2005 Chin. Phys. Lett. 22 2776
[22]	Tang Z J, Ren F, Peng T, Wang W B 2014 Acta Phys. Sin. 63 050505 (in Chinese) [唐舟进, 任峰, 彭涛, 王文博 2014 63 050505]
[23]	Wu X D, Wang Y N, Liu W T, Zhu Z Y 2011 Chin. Phys. 20 069201
[24]	Gottald G A, Melbourne I 2009 SIAM J. Appl. Dyn. Syst. 8 129
[25]	Gottald G A, Melbourne I 2009 Nonlinearity 22 1367
[26]	Kim H S, Eykholt R, Salas J D 1999 Physica D 127 48
[27]	Zhang H B, Sun X D, He Y L 2014 Acta Phys. Sin. 63 040505 (in Chinese) [张洪宾, 孙小端, 贺玉龙 2014 63 040505]
[28]	Grassberger P, Procaccia I 1983 Physica D 9 189
[29]	Wolf A, Swift J B, Swinney H L, Vastano J A 1985 Physica D 16 285
[30]	Suykens J A K, Vandevalle J 1999 Neural Process. Lett. 9 293
[31]	Kennedy J, Eberhart R 1995 Proceedings of the 1995 IEEE International Conference on Neural Networks (Piscataway, NJ: IEEE) p1942
[32]	Regis R G 2014 J. Comput. Sci. 5 12
[33]	Dong Z S, Zhang X Y, Zeng J C 2013 Trans. Can. Soc. Mech. Eng. 37 1189
[34]	Letting L K, Munda J L, Hamam Y 2012 Solar Energ. 86 1689

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