Author details

Mahmoud Ghofrani\* and Musaad Alolayan

\*Address all correspondence to: mrani@uw.edu

Electrical Engineering, Engineering and Mathematics Division, School of STEM, University of Washington Bothell, Bothell, WA, USA

### References

[1] Ding N, Besanger Y. Time series method for short-term load forecasting using smart metering in distribution systems. In: Proceeding of the IEEE Trondheim PowerTech; 2011. pp. 1-6


[18] Mellit A, Eleuch H, Benghanem M, Elaoun C, Massi Pavan AP. An adaptive model for predicting of global, direct and diffuse hourly solar irradiance. Energy Conversion and Management. 2010;51:771-782

[2] AR, MA and ARMA models, Available: www.math.unm.edu/~ghuerta/tseries/week4\_1.pdf [3] Inman R, Pedro H, Coimbra C. Solar forecasting methods for renewable energy integra-

[4] Wang W, Niu Z. Time series analysis of NASDAQ composite based on seasonal ARIMA model. In: Proceeding of the International Conference on Management and Service Sci-

[5] Contrearas-Reyes J, Palma W. Statistical analysis of autoregressive fractionally integrated

[6] Hatemi A. Multivariate tests for autocorrelation in the stable and unstable VAR models.

[7] Engle RF. Autoregressive conditional heteroscedasticity with estimates of the variance of

[8] Stepnicka M, Dvorak A, Pavliska V, Vavrickova L. Linguistic approach to time series analysis and forecasts. In: Proceeding of the IEEE International Conference on Fuzzy

[9] Reikard G. Predicting solar radiation at high resolutions: A comparison of time series

[10] Paoli C, Voyant C, Muselli M, Nivet M-L. Forecasting of preprocessed daily solar radia-

[11] Dazhi Y, Jirutitijaroen P, Walsh WM. Hourly solar irradiance time series forecasting using

[12] Martín L, Zarzalejo LF, Polo J, Navarro A, Marchante R, Cony M. Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants

[13] Touati T, Same A, Oukhellou L, Hourly solar irradiance forecasting based on machine learning models. In: Proceedings of the 2016 15th IEEE International Conference on

[14] Wu J, Chan CK. Prediction of hourly solar radiation using a novel hybrid model of

[15] Shams MB, Haji S, Salman A, Abdali H, Alsaffar A. Time series analysis of Bahrain's first

[16] Kärner O. ARIMA representation for daily solar irradiance and surface air temperature time series. Journal of Atmospheric and Solar—Terrestrial Physics. 2009;71:841-847 [17] Bacher P, Madsen H, Nielsen HA. Online short-term solar power forecasting. Solar

tion time series using neural networks. Solar Energy. 2010;84:2146-2160

tion. Progress in Energy and Combustion Science. Jul. 2013;39:535-576

moving average models. Computational Statistics. 2013;28(5):2309-2331

United Kingdom inflation. Econometrica. 1982;50(4):987-1007

ence; 2009. pp. 1-4

90 Time Series Analysis and Applications

Economic Modelling. 2004;21(4):661-683

forecasts. Solar Energy. 2009;83:342-349

cloud cover index. Solar Energy. 2012;86:3531-3543

energy production planning. Solar Energy. 2010;84:1772-1781

Machine Learning and Applications; 2016. pp. 441–446

hybrid renewable energy system. Energy. 2016;103:1-15

ARMA and TDNN. Solar Energy. 2011;85:808-817

Systems; July 2010. pp. 1-9

Energy. 2009;83:1772-1783

