范高锋,王伟胜,刘纯,等．基于人工神经网络的风电功率预测[J]．中国电机工程学报,2008,28(34)：118-123．Fan Gaofeng,Wang Weisheng,Liu Chun,et al．Wind power prediction based on artificial neural network [J]．Proceedings of the CSEE,2008,28(34)：118-123(in Chinese)．
[2]
王晓兰,王明伟．基于小波分解和最小二乘支持向量机的短期风速预测[J]．电网技术,2010,34(1)：179-184．Wang Xiaolan,Wang Mingwei．Short-term wind speed forecasting based on wavelet decomposition and least square support vector machine[J]．Power System Technology,2010,34(1)：179-184(in Chinese)．
[3]
李俊芳,张步涵,谢光龙,等．基于灰色模型的风速——风电功率预测研究[J]．电力系统保护与控制,2010,38(19)：151-159．Li Junfang,Zhang Buhan,Xie Guanglong,et al．Grey predictor models for wind speed-wind power prediction [J]．Power System Protection and Control,2010,38(19)：151-159(in Chinese)．
[4]
张翌晖,王贺,胡志坚,等．基于集合经验模态分解和改进极限学习机的短期风速组合预测研究[J]．电力系统保护与控制,2014,42(10)：29-34．Zhang Yihui,Wang He,Hu Zhijian,et al．A hybrid short-term wind speed forecasting model based on ensemble empirical mode decomposition and improved extreme learning machine[J]．Power System Protection and Control,2014,42(10)：29-34(in Chinese)．
[5]
李智,韩学山,杨明,等．基于分位点回归的风电功率波动区间分析[J]．电力系统自动化,2011,35(3)：83-87．Li Zhi,Han Xueshan,Yang Ming,et al．Wind power fluctuation interval analysis based on quantile regression [J]．Automation of Electric Power Systems,2011,35(3)：83-87(in Chinese)．
[6]
王彩霞,鲁宗相,乔颖,等．基于非参数回归模型的短期风电功率预测[J]．电力系统自动化,2010,34(16)：78-82,91．Wang Caixia,Lu Zongxiang,Qiao Ying,et al．Short-term wind power forecast based on non-parametric regression model[J]．Automation of Electric Power Systems,2010,34(16)：78-82,91(in Chinese)．
[7]
孙建波,吴小珊,张步涵．基于非参数核密度估计的风电功率区间预测[J]．水电能源科学,2013,31(9)：233-235,54．Sun Jianbo,Wu Xiaoshan,Zhang Buhan．Wind power interval prediction based on non-parametric kernel density estimation[J]．Water Resources and Power,2013,31(9)：233-235,54(in Chinese)．
[8]
Jeon J,Taylor J W．Using conditional kernel density estimation for wind power density forecasting[J]．Journal of the American Statistical Association,2012,107(497)：66-79．
[9]
Quan H,Srinivasan D,Khosravi A．Short-term load and wind power forecasting using neural network-based prediction intervals[J]．IEEE Transactions on Neural Networks and Learning Systems,2014,25(2)：303-315．
[10]
Pinson P,Tastu J．Discussion of “prediction intervals for short-term wind farm generation forecasts” and “combined nonparametric prediction intervals for wind power generation”[J]．IEEE Transactions on Sustainable Energy,2014,5(3)：1019-1020．
[11]
Huang G B,Wang D H,Lan Y．Extreme learning machines：a survey[J]．International Journal of Machine Learning and Cybernetics,2011,2(2)：107-122．
[12]
Huang G B,Zhu Q Y,Siew C -K．Extreme learning machine：Theory and applications[J]．Neurocomputing,2006,70(1-3)：489-501．
[13]
Huang G B．An insight into extreme learning machines：Random neurons,random features and kernels [J]．Cognitive Computation,2014,6(3)：376-390．
[14]
Cheng C,Tay W P,Huang G B．Extreme learning machines for intrusion detection[C]//Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN)．Brisbane,QLD：IEEE,2012：1-8．
[15]
Kennedy R,Eberhart J．Particle swarm optimization [C]//Proceedings of IEEE International Conference on Neural Networks．Perth,Australia：IEEE,1995,4：1942-1948．
[16]
Wan C,Xu Z,Pinson P,et al．Optimal prediction intervals of wind power generation[J]．IEEE Transactions on Power Systems,2014,29(3)：1166-1174．
[17]
章国勇,伍永刚,张洋,等．一种风电功率混沌时间序列概率区间简易预测模型[J]．物理学报,2014,63(13)：138801,doi:10.7498/aps.63.138801．Zhang Guoyong,Wu Yonggang,Zhang Yang,et al．A simple model for probabilistic interval forecasts of wind power chaotic time series[J]．Acta Physica Sinica,2014,63(13)：138801,doi:10.7498/aps.63.138801(in Chinese)．
[18]
Khosravi A,Nahavandi S,Creighton D,et al．Lower upper bound estimation method for construction of neural network-based prediction intervals[J]．IEEE Transactions on Neural Networks,2011,22(3)：337-346．
[19]
Khosravi A,Nahavandi S．Combined nonparametric prediction intervals for wind power generation[J]．IEEE Transactions on Sustainable Energy,2013,4(4)：849-856．
[20]
杨秀媛,肖洋,陈树勇．风电场风速和发电功率预测研究[J]．中国电机工程学报,2005,25(11)：1-5．Yang Xiuyuan,Xiao Yang,Chen Shuyong．Wind speed and generated power forecasting in wind farm [J]．Proceedings of the CSEE,2005,25(11)：1-5(in Chinese)．
[21]
Conejo A J,Plazas M A,Espinola R,et al．Day-ahead electricity price forecasting using the wavelet transform and ARIMA models[J]．IEEE Transactions on Power Systems,2005,20(2)：1035-1042．
