ITM Web Conf.
Volume 21, 2018Computing in Science and Technology (CST 2018)
|Number of page(s)||11|
|Published online||12 October 2018|
One day ahead forecasting of energy generating in photovoltaic systems
Rzeszow University of Technology, Department of Electrical and Computer Engineering Fundamentals, 35-959 Rzeszów, Poland
2 Rzeszow University of Technology, Department of Computer and Control Engineering, 35-959 Rzeszów, Poland
* Corresponding author: firstname.lastname@example.org
The article presents selected methods for forecasting energy generated by a solar system. Short-term forecasts are necessary in planning the work of renewable energy sources and their share in the energy market. Forecasting from the one-day horizon is one of the short-term forecasts. Rear-round prognostic models have been designed using various forecasting methods such as regression, neural networks or time series. On the basis of one day ahead forecasts the accuracy of designed models was assessed. The influence of selected weather factors on forecasts accuracy is also presented, only for models implemented by MLP neural networks. As well as the results of research on the impact of the model structure (as MLP neural network) on the accuracy of forecasts are presented.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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