|Autors: Zarkov, Z. Z., Stoyanov, L. S., Draganovska, I. I., Lazarov, V. D.|
Title: Application of ANN for solar radiation forecasting-case study of Oryahovo
Keywords: Artificial neural network, forecasting, solar radiance
Abstract: The forecasting of photovoltaic output power is one of the major problems for integration of large-scale solar systems for energy producing into the grid. The most challenging aspect of the solar forecasting is to predict the very short term of meteorological variables, such as solar radiance, ambient temperature, and cloud movement variations. Several forecast techniques for prediction of the solar irradiance are known, but generally the forecast techniques could be classified in three main categories physical, statistical and hybrid method. This paper presents an application of ANN for forecasting of the solar radiance. For this purpose are used data from Oryahovo, Bulgaria. After the training of the ANN it is verified by comparison of the forecasted values with measured data. The precision is satisfying with relative root mean square error of 5%.
1. Prema, V., Bhaskar, M.S., Almakhles, D., Gowtham, N., Rao, K.U., Critical Review of Data, Models and Performance Metrics for Wind and Solar Power Forecast, IEEE Access, vol. 10, pp. 667-688 - 2022 - в издания, индексирани в Scopus или Web of Science
Вид: публикация в национален форум с межд. уч., публикация в реферирано издание, индексирана в Scopus