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船舶电力推进系统电力负荷混沌特性分析及预测 被引量:2

Chaotic characters of power load and its forecasting for marine electric propulsion system
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摘要 为实现船舶电力推进系统功耗的最优控制,提高船舶运行的经济性,建立了基于正则化的电力负荷混沌局域预测模型.运用相空间重构理论对船舶电力推进系统电力负荷进行单变量时间序列相空间重构,计算吸引子的Lyapunov指数,验证船舶电力推进系统电力负荷具有混沌特性,进而构建更为精准的由船舶电力负荷及其影响因素构成的多变量时间序列相空间.实验结果表明,该预测模型是有效的,且具有较高的预测精度. A local prediction model of chaotic time series for power load was set up to realize optimal control for low-power consumption while promoting the operational economy in marine electric propulsion system. Phase space reconstruction of single variable time series was used in power load in marine electric propulsion system based on phase space reconstruction theory, and the Lyapunov exponents of the attractors were calculated, which proved that the power load has chaotic characteristics. Moreover, a more accurate multivariable time series phase space forecasting model was reconstructed. Experimental results show that the proposed model is effective with high prediction precision.
作者 赵敏 樊印海
出处 《大连海事大学学报》 EI CAS CSCD 北大核心 2008年第2期126-128,共3页 Journal of Dalian Maritime University
基金 "十五"重大技术装备研制项目(JDRo-Z4-01)
关键词 船舶电力推进系统 电力负荷 混沌特性 marine electric propulsion system power load chaotic characters
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参考文献7

  • 1KANTZ H,SCHREIBER T.Nonlinear time series analysis[M].Cambridge:Cambridge University Press,1997.
  • 2ABARBANEL H D I,NAOKI MASUDA,RABINOVICH M I,et al.Distribution of mutual information[J].Physics Letters A,2001,281:368-373.
  • 3KENNEL M B,BROWN R,ALRARBANEL H D I.Determining embedding dimension for phase-space reconstruction using a geometrical construction[J].Physical Review A,1992,45(2):3403-3411.
  • 4ROSENSTEIN M T,COLLINS J J,DE LUCA C J.A practical method for calculating largest Lyapunov exponents from small data sets[J].Physica D,1993,65:117-134.
  • 5YANG H M,DUAN X Z.Chaotic characteristics of dectricity price and its forecasting model[C]//IEEE CCECE,Montreal:[s.n.].2003:659-662.
  • 6PORPORATO A,RIDOLFI L.Multivariate nonlinear prediction of river flows[J].Journal of Hydrology,2001,248:109-122.
  • 7JAYAWARDEN A W,LI W K,XUP.Neighborhood selection for local modeling and prediction of hydrological time series[J].Journal of Hydrology,2002,258:40-57.

同被引文献21

  • 1王锡淮,朱思锋.基于支持向量机的船舶电力负荷预测[J].中国电机工程学报,2004,24(10):36-39. 被引量:40
  • 2YANG H M, UAN X Z. Chaotic characteristics of electricity price and its forecasting model [J]. IEEE CCECE Montreal, 2003. 659-662.
  • 3Grassberger P, rocaceia I, imension and entropy or strange attractors from a fluctuating dyamics approach [J]. Physica,1984(13D): 34-35.
  • 4N H Packard, P Crutchfield, D Farmer, R S Shaw. Geometry from a time series [J]. Phys. Rev Lett., 1980, 45: 71.
  • 5吕金虎,陆君安,陈士华.混沌时间序列分析及其应用[M].武汉大学出版社,2003.
  • 6M T Martin, F Pennini, A Plastino. Fisher's information and the analysis of complex signals [A]. Phys.Lett.A [C]. 1999, 256:173-180.
  • 7Takens F. Determing strange attractors in turbulence [J]. Lecture Notes in Math, 1981, 89(8): 366-381.
  • 8Liaoyue Cao. Practical method for determing the minimum embedding dimension of a scalar time series [D]. Pysica D, 1997.3-50.
  • 9Michael T. Rosenstein, ames J Collins, Carlo J. De Luca. A practical method for calculating largest Lyapunovexponents from small data sets [C]. 1992.
  • 10赵敏,樊印海,孙辉.电力推进船舶电力负荷的多变量混沌局部预测[J].系统仿真学报,2008,20(11):2797-2799. 被引量:10

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