In recent years, as the share of solar power in the electrical grid has been increasing, accurate methods for forecasting solar irradiance have become necessary to manage the electrical grid. More specifically, as solar generators are geographically dispersed, it is very important to have general models that can predict solar irradiance without the need of ground data. In this paper, we propose a novel technique that can accomplish that: using satellite images, the proposed model is able to forecast solar irradiance without the need of ground measurements. To illustrate the performance of the proposed model, we consider 15 locations in The Netherlands, and we show that the proposed model is as accurate as local models that are individually trained with ground data.
|Title of host publication||Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018)|
|Place of Publication||Piscataway, NJ, USA|
|Publication status||Published - 2018|
|Event||CDC 2018: 57th IEEE Conference on Decision and Control - Miami, United States|
Duration: 17 Dec 2018 → 19 Dec 2018
|Conference||CDC 2018: 57th IEEE Conference on Decision and Control|
|Period||17/12/18 → 19/12/18|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
- Predictive models
- Data models
- Computational modeling
- Weather forecasting
- Numerical models