Ortiz, R. E. I. and Peng F. Z. (2006) Algorithms to esti-mate the temperature and effective irradiance level over a photovoltaic module using the fixed point theorem. Power Electronics Specialists Conference, PESC’06, 37th IEEE, 1–4.

has been cited by the following article:

• TITLE: Study of daily solar Irradiance forecast based on chaos optimization neural networks

  AUTHORS: Shuang-Hua Cao, Jian-Bo Chen, Wen-Bing Weng, Jia-Cong Cao

  KEYWORDS: Daily Solar Irradiance Forecast; Wavelet Transformation; Chaos Optimization Neural Networks

  JOURNAL NAME: Natural Science, Vol.1 No.1, July 2, 2009

  ABSTRACT: In this works, artificial neural network is com-bined with wavelet analysis for the forecast of solar irradiance. This method is characteristic of the preprocessing of sample data using wavelet transformation for the forecast, i.e., the data se-quence of solar irradiance as the sample is first mapped into several time-frequency domains, and then a chaos optimization neural network is established for each domain. The forecasted so-lar irradiance is exactly the algebraic sum of all the forecasted components obtained by the re-spective networks, which correspond respec-tively the time-frequency domains. On the basis of combination of chaos optimization neural network and wavelet analysis, a model is devel-oped for more accurate forecasts of solar irradi-ance. An example of the forecast of daily solar irradiance is presented in the paper, the historical daily records of solar irradiance in Shanghai constituting the data sample. The results of the example show that the accuracy of the method is more satisfacto