Model Estimation for Solar Generation Forecasting using Cloud Cover Data
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2019
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909434969587712 |
|---|---|
| author | Pepe, Daniele Bianchini, Gianni Vicino, Antonio |
| author_facet | Pepe, Daniele Bianchini, Gianni Vicino, Antonio |
| contents | This paper presents a parametric model approach to address the problem of photovoltaic generation forecasting in a scenario where measurements of meteorological variables, i.e., solar irradiance and temperature, are not available at the plant site. This scenario is relevant to electricity network operation, when a large number of PV plants are deployed in the grid. The proposed method makes use of raw cloud cover data provided by a meteorological service combined with power generation measurements, and is particularly suitable in PV plant integration on a large-scale basis, due to low model complexity and computational efficiency. An extensive validation is performed using both simulated and real data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1901_07525 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | Model Estimation for Solar Generation Forecasting using Cloud Cover Data Pepe, Daniele Bianchini, Gianni Vicino, Antonio Systems and Control This paper presents a parametric model approach to address the problem of photovoltaic generation forecasting in a scenario where measurements of meteorological variables, i.e., solar irradiance and temperature, are not available at the plant site. This scenario is relevant to electricity network operation, when a large number of PV plants are deployed in the grid. The proposed method makes use of raw cloud cover data provided by a meteorological service combined with power generation measurements, and is particularly suitable in PV plant integration on a large-scale basis, due to low model complexity and computational efficiency. An extensive validation is performed using both simulated and real data. |
| title | Model Estimation for Solar Generation Forecasting using Cloud Cover Data |
| topic | Systems and Control |
| url | https://arxiv.org/abs/1901.07525 |