Open Access
E3S Web Conf.
Volume 51, 2018
2018 3rd International Conference on Advances on Clean Energy Research (ICACER 2018)
Article Number 02003
Number of page(s) 6
Section Solar Energy Utilization and Power Generation Technology
Published online 24 August 2018
  1. V. Margaret, J. Jose. Exponential Smoothing Models for Prediction of Solar Irradiance. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (An ISO 3297: 2007 Certified Organization) Vol. 4, Issue 2, February 2015. [Google Scholar]
  2. D.A. Snegirev, S.A. Eroshenko, R.T. Valiev, A.I. Khalyasmaa. Algorithmic realization of short-term solar power plant output forecasting. Proceedings of 2017 IEEE 2nd International Conference on Control in Technical Systems, CTS 2017. Pp. 228-231. [Google Scholar]
  3. C. Severiano, F. G. Guimarães and M. W. Cohen, “Very short-term solar forecasting using multi-agent system based on Extreme Learning Machines and data clustering,” 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, 2016, pp. 1-8. [Google Scholar]
  4. C.A. Severiano, P. C. L. Silva, H. J. Sadaei and F. G. Guimarães, “Very short-term solar forecasting using fuzzy time series,” 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Naples, 2017, pp. 1-6. [Google Scholar]
  5. A.D. Orjuela-Cañón, J. Hernández and C. R. Rivero, “Very short term forecasting in global solar irradiance using linear and nonlinear models,” 2017 IEEE Workshop on Power Electronics and Power Quality Applications (PEPQA), Bogota, 2017, pp. 1-5. [Google Scholar]
  6. S. Gupta, N. A. Shrivastava, A. Khosravi and B. K. Panigrahi, “Wind ramp event prediction with parallelized gradient boosted regression trees,” 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, 2016, pp. 5296-5301. [CrossRef] [Google Scholar]
  7. W. Glassley, J. Kleissl. Current state of the art in solar forecasting. California Renewable Energy Collaborative Final Report. 2013. [Google Scholar]
  8. V. Prema. K. Uma Rao. Development of statistical time series models for solar power prediction. Renewable energy. 2015. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.