Abstract：The randomness and volatility of wind power time series make it difficult to achieve the desired multi-step prediction accuracy.Therefore, a model of real-time prediction for wind power based on empirical mode decomposition(EMD) and set pair analysis is presented.The proposed wind power sequences are firstly decomposed into a series of functions with more stationary variation by the EMD technique.Then these functions are divided into three components(high-middle-low frequency components) according to their run-lengths by the extreme point division method.Finally, three prediction models are built under the basis of their respective variation rules, and the results of three prediction models are reconstructed with the original wind power prediction value, this model achieves multi-step prediction by rolling prediction.The data from Three different wind farms with different installed capacity are used for simulate experiment.The results show that the proposed approach possesses with higher accuracy and the prediction performance is satisfied.
杨茂,陈郁林. 基于EMD分解和集对分析的风电功率实时预测[J]. 电工技术学报, 2016, 31(21): 86-93.
Yang Mao,Chen Yulin. Real-Time Prediction for Wind Power Based on EMD and Set Pair Analysis. Transactions of China Electrotechnical Society, 2016, 31(21): 86-93.
[1] 薛禹胜,雷兴,薛峰,等.关于风电不确定性对电力系统影响的评述[J].中国电机工程学报,2014,34(29):5029-5040. Xue Yusheng,Lei Xing,Xue Feng,et al.A review on impacts of wind power uncertainties on power systems[J].Proceedings of CSEE,2014,34(29):5029-5040. [2] 杨锡运,孙宝君,张新房,等.基于相似数据的支持向量机短期风速预测仿真研究[J].中国电机工程学报,2012,32(4):35-41. Yang Xiyun,Sun Baojun,Zhang Xinfang,et al.Short-term wind speed combined prediction for wind farms based on wavelet transform[J].Proceedings of CSEE,2012,32(4):35-41. [3] Cuo Lan,Zhang Yongxin,Wang Qingchun,et al.Climate change on the northern Tibetan Plateau during 1957-2009:Spatial patterns and possible mechanisms[J].Journal of Climate,2013,26(1):85-109. [4] 王丽婕,冬雷,高爽.基于多位置NWP与主成分分析的风电功率短期预测[J].电工技术学报,2015,30(5):79-84. Wang Lijie,Dong Lei,Gao Shuang.Wing power short-term prediction based on principal component analysis of NWP of multiple locations[J].Transactions of China Electrotechnical Society,2015,30(5):79-84. [5] 李丽,叶林.基于改进持续法的短期风电功率预测[J].农业工程学报,2010,26(12):182-187. Li Li,Ye Lin.Short-term wind power forecasting based on an improved persistence approach[J].Transactions of the Chinese Society of Agricultural Engineering,2010,26(12):182-187. [6] 冬雷,王丽婕,郝颖,等.基于自回归滑动平均模型的风力发电容量预测[J].太阳能学报,2011,32(5):617-622. Dong Lei,Wang Lijie,Hao Ying,et al.Prediction of wind power generation based on autoregressive moving average model[J].Acta Energiae Solaris Sinica,2011,32(5):617-622. [7] 罗毅,刘峰,刘向杰.基于主成分—遗传神经网络的短期风电功率预测[J].电力系统保护与控制,2012,23(40):47-53. LuoYi,Liu Feng,Liu Xiangjie.Short-term wind power prediction based on principal component analysis and genetic neural network[J].Power System Protection and Control,2012,23(40):27-53. [8] 王贺,胡志坚,仉梦林.基于模糊信息粒化和最小二乘支持向量机的风电功率波动范围组合预测模型[J].电工技术学报,2014,29(12):218-224. Wang He,Hu Zhijian,Zhang Menglin.A combined forecasting model for range of wind power fluctuationbased on fuzzy information granulation and least squares support vector machine[J].Transactions of China Electrotechnical Society,2014,29(12):218-224. [9] 杨茂,熊昊,严干贵,等.基于数据挖掘和模糊聚类的风电功率实时预测研究[J].电力系统保护与控制,2013,41(1):1-6. Yang mao,Xiong Hao,Yan Gangui,et al.Real-time prediction of wind power based on data mining and fuzzy clustering[J].Power System Protection and Control,2013,41(1):1-6. [10]杨茂,贾云彭,钱为,等.基于动态权重的风电功率组合预测方法研究[J].东北电力大学学报,2013,33(1-2):131-136. Yang Mao,Jia Yunpeng,Qian Wei,et al.A combination method research for wind power predication based on dynamic weight[J].Journal of Northeast Dianli University,2013,33(1-2):131-136. [11]国家能源局.风电厂功率预测预报管理暂行办法[S].北京:国家能源局,2011. [12]刘兴杰,米增强,杨奇逊,等.一种基于EMD的短期风速多步预测方法[J].电工技术学报,2010,25(4):165-170. Liu Xingjie,Mi Zengqiang,Yang Qixun,et al.A novel multi-step prediction for wind speed based on EMD[J].Transactions of China Electrotechnical Society,2010,25(4):165-170. [13]Huang N E,Shen Z,Long S,et al.The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society of London Series A,1998,454:903-995. [14]赵克勤.集对分析及其初步应用[J].大自然探索,2000,13(1):4-8. Zhao Keqin.Set pair analysis and its preliminary application[J].Exploration of Nature,2000,13(1):4-8. [15]汪明武.集对分析耦合方法与应用[M].北京:科学出版社,2014. [16]高洁,盛昭瀚.集对分析聚类预测法及其应用[J].系统工程学报,2002,17(5):458-462. Gao Jie,Sheng Zhaohan.Method and application of set pair analysis classified prediction[J].Journal of Systems Engineering,2002,17(5):458-462. [17]郭钰锋,孙頔,于继来,等.集对分析理论在风电场风速区间预测中的应用[J].电力系统自动化,2014,38(2):6-11. Guo Yufeng,Sun Di,Yu Jilai,et al.Application of set pair analysis in wind speed interval prediction for wind farms[J].Automation of Electric Power Systems,2014,38(2):6-11. [18]杨茂,王东,严干贵,等.风电功率波动特性中的周期性研究[J].太阳能学报,2013,34(11):2020-2026. Yang Mao,Wang Dong,Yan Gangui,et al.study on periodicity for wind power fluctuations characteristics[J].Acta Energiae Solaris Sinica,2013,34(11):2020-2026. [19]严干贵,王东,杨茂,等.两种风电功率多步预测方式的分析及评价[J].东北电力大学学报,2013,33(增1):126-130. Yan Gangui,Wang Dong,Yang Mao,et al.The analysis and evaluation of two ways for multi-step wind power prediction[J].Journal of Northeast Dianli University,2013,33(S1):126-130. [20]杨茂,孙涌,孙兆键,等.风电场大规模数据管理系统设计与研发[J].东北电力大学学报,2014,34(2):27-31. Yang Mao,Sun Yong,Sun Zhaojian,et al.Design and development of large-scale data management system of wind farm[J].Journal of Northeast Dianli University,2013,34(2):27-31.
2016, Vol. 31 
