Power characteristics of PV ensembles: experiences from the combined power production of 100 grid connected PV systems distributed over the area of Germany

By E. Wiemken, Hans-Georg Beyer, W. Heydenreich, K. Kiefer. 2001

173 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/0507715bed272643fb064431be9251a57e3b6df9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Can Wan
2. Javier Marcos
3. Zhao Xu
4. Yonghua Song
5. Jian Zhao
6. O. Perpiñán
7. Zechun Hu
8. Eduardo Lorenzo

In Electrical and Electronic Engineering

1. Can Wan
2. Zhao Xu
3. Yonghua Song
4. Jian Zhao
5. Zechun Hu
6. Jin Lin

Citations in the corpus

• Electrical Power Fluctuations in a Network of DC/AC inverters in a Large PV Plant: relationship between correlation, distance and time scale (2013, methodology): “[3] worked with one year of 1 min data from 100 PV sites (totalling 243 kWp) spread over Germany.”
• Photovoltaic and solar power forecasting for smart grid energy management (2015, background): “Short-time fluctuation of PV outputs can be extremely large, depending on weather conditions, such as cloud passing [58]–[60].”