A hierarchical Bayesian regression model for predicting summer residential electricity demand across the U.S.A.

作者: Siyan Wang , Xun Sun , Upmanu Lall

DOI: 10.1016/J.ENERGY.2017.08.076

关键词:

摘要: … be the inverse Wishart distribution with scale matrices of Λ 1 … the scale matrix Λ 0 and Λ 1 are initiated as diagonal matrices … value of posterior distribution of regression coefficient of CDD…

参考文章(37)
J. V. Ringwood, D. Bofelli, F. T. Murray, Forecasting Electricity Demand on Short, Medium and Long Time Scales Using Neural Networks Journal of Intelligent and Robotic Systems. ,vol. 31, pp. 129- 147 ,(2001) , 10.1023/A:1012046824237
Badi H. Baltagi, Georges Bresson, Alain Pirotte, Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators Economics Letters. ,vol. 76, pp. 375- 382 ,(2002) , 10.1016/S0165-1765(02)00065-4
Jihoon Min, Zeke Hausfather, Qi Feng Lin, A High-Resolution Statistical Model of Residential Energy End Use Characteristics for the United States Journal of Industrial Ecology. ,vol. 14, pp. 791- 807 ,(2010) , 10.1111/J.1530-9290.2010.00279.X
Andrew Harvey, Siem Jan Koopman, Forecasting Hourly Electricity Demand Using Time-Varying Splines Journal of the American Statistical Association. ,vol. 88, pp. 1228- 1236 ,(1993) , 10.1080/01621459.1993.10476402
Thomas Mestekemper, Göran Kauermann, Michael S. Smith, A comparison of periodic autoregressive and dynamic factor models in intraday energy demand forecasting International Journal of Forecasting. ,vol. 29, pp. 1- 12 ,(2013) , 10.1016/J.IJFORECAST.2012.03.003
Orhan Büyükalaca, Hüsamettin Bulut, Tuncay Yılmaz, Analysis of variable-base heating and cooling degree-days for Turkey Applied Energy. ,vol. 69, pp. 269- 283 ,(2001) , 10.1016/S0306-2619(01)00017-4