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为揭示风电功率序列内在的动态特性, 利用非线性方法对风电时间序列混沌特性进行识别, 为对风电功率进行预测提供了基础.首先对某风电场的风电功率时间序列的日相关性进行了分析;然后在相空间重构的基础上计算了风电序列的最大Lyapunov指数, 验证了风电时间序列的混沌特性;由于采用Volterra滤波器多步预测法对风电功率进行超短期预测误差较大, 利用局域多步预测法以及最大Lyapunov指数法的预测结果并结合加权马尔科夫链和有序算子对Volterra滤波器的预测结果进行校正.最后以某实际风电场的风电功率预测为算例, 仿真结果表明校正预测模型有效的提高了预测精度, 其为利用Volterra滤波器多步法进行风电预测提供了有益的参考.
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关键词:
- 风电预测 /
- 混沌 /
- Volterra滤波器多步预测 /
- 加权马尔科夫链
In order to reveal the internal dynamic property of wind power time series the nonlinear analysis method is used to identify the chaotic property of wind power set which is the basis for the prediction of the wind power time series. Firstly day correlation property on wind power time series of a certain wind farmer is analyzed. Secondly the largest Lyapunov exponent of wind power set is calculated on the basis of phase space construction to verify the presence of chaos in wind power time series. The ultra-short-term predicted of wind power would produce larger errors by using the Volterra filter multi-step prediction so the predicted results of Volterra filter are corrected by combining the results predicted by Local-region Multi-steps Method and the largest Lyapunov exponent method with weighted Markov chain and ordered operator. Finally the prediction on wind power of a certain wind farmer is presented and the simulation results illustrate that the correction forecasting model improves high predictive accuracy effectively, which provides a useful reference for wind power prediction by the Volterra filter multi-step method.-
Keywords:
- wind power prediction /
- chaos /
- Volterra filter multi-step prediction /
- weighted Markov chain
[1] Mcelroy M B, Lu X 2009 Science 325 1378
[2] Feng S L, Wang W S, Liu C, Dai H Z 2010 Proceedings of the CSEE 30 1 (in Chinese)[冯双磊, 王伟胜, 刘纯, 戴慧珠 2010 中国电机工程学报 30 1]
[3] Yang X Y, Xiao Y, Chen S Y 2005 Proceedings of the CSEE 25 1 (in Chinese) [杨秀媛, 肖洋, 陈树勇 2005中国电机工程学报 25 1]
[4] Pan D F, Liu H, Li Y F 2008 Proceedings of the CSEE 28 87 (in Chinese) [潘迪夫, 刘辉, 李燕飞 2008 中国电机工程学报 28 87]
[5] Shi H T, Yang J L, Ding M S, Wang J M 2011 Automation of Electric Power Systems 35 44 (in Chinese)[师洪涛, 杨静玲, 丁茂生, 王金梅 2011 电力系统自动化 35 44]
[6] Zhou S L, Mao M Q, Su J H 2011 Proceedings of the CSEE 31 10(in Chinese)[周松林, 茆美琴, 苏建徽 2011 中国电机工程学报 31 10]
[7] Zhang Y, Guan W 2009 Acta Phys. Sin. 58 754(in Chinese)[张勇, 关伟2009 58 754]
[8] Meng Q F, Zhang Q, Mu W Y 2006 Acta Phys. Sin. 55 1666 (in Chinese)[孟庆芳, 张强, 牟文英 2006 55 1666]
[9] Zhang J S, Xiao X C 2000 Acta Phys. Sin. 49 403 (in Chinese) [张家树, 肖先赐2000 49 403]
[10] Zhang J S, Xiao X C 2001 Acta Phys. Sin. 50 1248 (in Chinese) [张家树, 肖先赐2000 50 1248]
[11] Zhang J S, Xiao X C 2000 Acta Phys. Sin. 49 2333 (in Chinese) [张家树, 肖先赐 2000 49 2333]
[12] Du J, Cao Y J, Liu Z J, Xu L Z, Jiang Q Y, Guo C X, Lu J G 2009 Acta Phys. Sin. 58 5997 (in Chinese) [杜杰, 曹一家, 刘志坚, 徐立中, 江全元, 郭创新, 陆金桂 2009 58 5997]
[13] Gan J C, Xiao X C 2003 Acta Phys. Sin. 52 1102 (in Chinese) [甘建超, 肖先赐 2003 52 1102]
[14] Gan J C, Xiao X C 2003 Acta Phys. Sin. 52 1097 (in Chinese) [甘建超, 肖先赐 2003 52 1097]
[15] Takens F 1981 Dynamical System and Turbulence, Lecture Notes in Mathematics (Vol. 898) (Berlin: Springer-Verlag) p230
[16] Han M 2007 Predict Theory and Method of Chaotic Times Series (Vol. 1) (Beijing: China WaterPower Press) p168 (in Chinese) [韩敏 2007 混沌时间序列预测理论与方法 (第1卷) (北京: 中国水利水电出版社) 第168页]
[17] Zhang Y M, Qi Y G 2011 Acta Phys. Sin. 60 100508 (in Chinese) [张永明, 齐维贵 2011 60 100508]
[18] Farmer J D, Sidorowich J J 1987 Phys. Rev. Let. 59 845
[19] Cai M L, Cai, F, Shi A G 2004International Sym. on Neural Networks Dalian, China August, 2004 p418
[20] Mao L F, Yao J G, Jin Y S, Chen H L, Li W J, Guan S L 2010 Proceedings of the CSEE 30 53 (in Chinese) [毛李帆, 姚建刚, 金永顺, 陈华林, 李文杰, 关石磊 2010 中国电机工程学报 30 53]
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[1] Mcelroy M B, Lu X 2009 Science 325 1378
[2] Feng S L, Wang W S, Liu C, Dai H Z 2010 Proceedings of the CSEE 30 1 (in Chinese)[冯双磊, 王伟胜, 刘纯, 戴慧珠 2010 中国电机工程学报 30 1]
[3] Yang X Y, Xiao Y, Chen S Y 2005 Proceedings of the CSEE 25 1 (in Chinese) [杨秀媛, 肖洋, 陈树勇 2005中国电机工程学报 25 1]
[4] Pan D F, Liu H, Li Y F 2008 Proceedings of the CSEE 28 87 (in Chinese) [潘迪夫, 刘辉, 李燕飞 2008 中国电机工程学报 28 87]
[5] Shi H T, Yang J L, Ding M S, Wang J M 2011 Automation of Electric Power Systems 35 44 (in Chinese)[师洪涛, 杨静玲, 丁茂生, 王金梅 2011 电力系统自动化 35 44]
[6] Zhou S L, Mao M Q, Su J H 2011 Proceedings of the CSEE 31 10(in Chinese)[周松林, 茆美琴, 苏建徽 2011 中国电机工程学报 31 10]
[7] Zhang Y, Guan W 2009 Acta Phys. Sin. 58 754(in Chinese)[张勇, 关伟2009 58 754]
[8] Meng Q F, Zhang Q, Mu W Y 2006 Acta Phys. Sin. 55 1666 (in Chinese)[孟庆芳, 张强, 牟文英 2006 55 1666]
[9] Zhang J S, Xiao X C 2000 Acta Phys. Sin. 49 403 (in Chinese) [张家树, 肖先赐2000 49 403]
[10] Zhang J S, Xiao X C 2001 Acta Phys. Sin. 50 1248 (in Chinese) [张家树, 肖先赐2000 50 1248]
[11] Zhang J S, Xiao X C 2000 Acta Phys. Sin. 49 2333 (in Chinese) [张家树, 肖先赐 2000 49 2333]
[12] Du J, Cao Y J, Liu Z J, Xu L Z, Jiang Q Y, Guo C X, Lu J G 2009 Acta Phys. Sin. 58 5997 (in Chinese) [杜杰, 曹一家, 刘志坚, 徐立中, 江全元, 郭创新, 陆金桂 2009 58 5997]
[13] Gan J C, Xiao X C 2003 Acta Phys. Sin. 52 1102 (in Chinese) [甘建超, 肖先赐 2003 52 1102]
[14] Gan J C, Xiao X C 2003 Acta Phys. Sin. 52 1097 (in Chinese) [甘建超, 肖先赐 2003 52 1097]
[15] Takens F 1981 Dynamical System and Turbulence, Lecture Notes in Mathematics (Vol. 898) (Berlin: Springer-Verlag) p230
[16] Han M 2007 Predict Theory and Method of Chaotic Times Series (Vol. 1) (Beijing: China WaterPower Press) p168 (in Chinese) [韩敏 2007 混沌时间序列预测理论与方法 (第1卷) (北京: 中国水利水电出版社) 第168页]
[17] Zhang Y M, Qi Y G 2011 Acta Phys. Sin. 60 100508 (in Chinese) [张永明, 齐维贵 2011 60 100508]
[18] Farmer J D, Sidorowich J J 1987 Phys. Rev. Let. 59 845
[19] Cai M L, Cai, F, Shi A G 2004International Sym. on Neural Networks Dalian, China August, 2004 p418
[20] Mao L F, Yao J G, Jin Y S, Chen H L, Li W J, Guan S L 2010 Proceedings of the CSEE 30 53 (in Chinese) [毛李帆, 姚建刚, 金永顺, 陈华林, 李文杰, 关石磊 2010 中国电机工程学报 30 53]
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