2268. A High-Resolution Downscaling Approach for Solar Irradiance Using Statistical Parameter Matching
Invited abstract in session WC-44: Improving data and methods for energy system investment, stream Energy Economics & Management.
Wednesday, 12:30-14:00Room: Newlyn 1.01
Authors (first author is the speaker)
| 1. | Olalekan Omoyele
|
| ICE-2, Forschungzentrum Jülich | |
| 2. | Maximilian Hoffmann
|
| Forschungszentrum Jülich GmbH | |
| 3. | Jann Weinand
|
| Karlsruhe Institute of Technology (IIP) | |
| 4. | Miguel Larrañeta
|
| Universidad de Sevilla | |
| 5. | Jochen Linßen
|
| Forschungszentrum Jülich |
Abstract
The limited intra-hour variability of globally available hourly renewable energy system data leads to inaccuracies in the modeling of renewable energy systems. This work, therefore, presents a methodology to increase the temporal resolution of the global horizontal irradiance from one hour to one minute using non-dimensional irradiance and parameters matching for arbitrary locations. The methodology is validated using statistical methods and energy system modeling in self-sufficient buildings. The hourly annual normalized root mean square error and Kolmogorov-Smirnov Integral range from 6 - 12% and 0.1 - 0.84, respectively, for different locations consisting of varying weather conditions. The energy system optimization results of the synthetic data demonstrate superiority in terms of cost and feasibility relative to the average hourly resolution data. The use of synthetic minute resolution data has been shown to significantly improve the design accuracy of dynamic components such as inverters (where underestimation in capacity is up to 58%) and storage systems. The developed methodology facilitates more reliable energy system modeling.
Keywords
- Capacity Planning
- Optimization Modeling
- OR in Energy
Status: accepted
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