Abstract
The capacity of renewable energy sources constantly increases world-wide and challenges the maintenance of the electric balance between power demand and supply. To allow for a better integration of solar energy supply into the power grids, a lot of research was dedicated to the development of precise forecasting approaches. However, there is still no straightforward and easy-to-use recommendation for a standardized forecasting strategy. In this paper, a classification of solar forecasting solutions proposed in the literature is provided for both weather- and energy forecast models. Subsequently, we describe our idea of a standardized forecasting process and the typical parameters possibly influencing the selection of a specific model. We discuss model combination as an optimization option and evaluate this approach comparing different statistical algorithms against flexible hybrid models in a case study.
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Acknowledgment
The work presented in this paper was funded by the European Regional Development Fund (EFRE) and the Free State of Saxony under the grant agreement number 100081313 and co-financed by Robotron Datenbank-Software GmbH. We thank Claudio Hartmann and Andreas Essbaumer for supporting our work.
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Ulbricht, R., Hahmann, M., Donker, H., Lehner, W. (2014). Systematical Evaluation of Solar Energy Supply Forecasts. In: Woon, W., Aung, Z., Madnick, S. (eds) Data Analytics for Renewable Energy Integration. DARE 2014. Lecture Notes in Computer Science(), vol 8817. Springer, Cham. https://doi.org/10.1007/978-3-319-13290-7_9
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DOI: https://doi.org/10.1007/978-3-319-13290-7_9
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