Refine
Year of publication
- 2017 (31) (remove)
Document Type
- Conference proceeding (31) (remove)
Language
- English (31)
Is part of the Bibliography
- yes (31) (remove)
Institute
- Technik (31) (remove)
Publisher
- IEEE (19)
- Technische Universität Berlin (3)
- Springer (2)
- British Institute of Non-Destructive Testing (1)
- Newcastle University (1)
- SPIE (1)
- VDE Verlag (1)
- VDE Verlag GmbH (1)
- WIP (1)
The purpose of this article is to provide insight of a new simple forecasting method based on a state-estimation algorithm known as the Kalman filter. While the accuracy of such algorithm is not comparable to state-of-the-art forecasting algorithms for PV-power production it does not require any internet connection, eyefish cameras or time intensive training. The algorithm was tested with several months of real high-resolution data with adequate results for the intended applications. The minimization of the necessary spinning reserve on a PV-diesel hybrid system to increase the solar fraction and reduce diesel consumption.