Cloud-tracking methodology for intra-hour DNI forecasting

By S. Quesada-Ruiz, Yinghao Chu, Joaquín Tovar-Pescador, H. Pedro, Carlos F. M. Coimbra. 2014

165 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/2baf21863bdec709545ce906d1c33044ddd88143

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. João P. S. Catalão
2. Fei Wang
3. Zengqiang Mi

In Computer Vision and Pattern Recognition

1. M. Shafie‐khah
2. João P. S. Catalão
3. Bri-Mathias S. Hodge
4. Fei Wang
5. Liu Chun
6. Zengqiang Mi
7. Zhao Zhen
8. José M. F. Moura

In Environmental Engineering

1. Fei Wang

Citations in the corpus

• Image phase shift invariance based cloud motion displacement vector calculation method for ultra-short-term solar PV power forecasting (2018, methodology): “Especially in cloudy weather conditions, the solar irradiance on 53 the ground can fluctuant significantly at the minute level, which brings a great many difficulties for solar irradiance forecasting 54 in intra-hour [11,12] instead of hourly [13] or daily [14] time scales.”