کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
772776 897737 2008 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Study of hourly and daily solar irradiation forecast using diagonal recurrent wavelet neural networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
پیش نمایش صفحه اول مقاله
Study of hourly and daily solar irradiation forecast using diagonal recurrent wavelet neural networks
چکیده انگلیسی

An accurate forecast of solar irradiation is required for various solar energy applications and environmental impact analyses in recent years. Comparatively, various irradiation forecast models based on artificial neural networks (ANN) perform much better in accuracy than many conventional prediction models. However, the forecast precision of most existing ANN based forecast models has not been satisfactory to researchers and engineers so far, and the generalization capability of these networks needs further improving. Combining the prominent dynamic properties of a recurrent neural network (RNN) with the enhanced ability of a wavelet neural network (WNN) in mapping nonlinear functions, a diagonal recurrent wavelet neural network (DRWNN) is newly established in this paper to perform fine forecasting of hourly and daily global solar irradiance. Some additional steps, e.g. applying historical information of cloud cover to sample data sets and the cloud cover from the weather forecast to network input, are adopted to help enhance the forecast precision. Besides, a specially scheduled two phase training algorithm is adopted. As examples, both hourly and daily irradiance forecasts are completed using sample data sets in Shanghai and Macau, and comparisons between irradiation models show that the DRWNN models are definitely more accurate.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy Conversion and Management - Volume 49, Issue 6, June 2008, Pages 1396–1406
نویسندگان
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