Image phase shift invariance based cloud motion displacement vector calculation method for ultra-short-term solar PV power forecasting

By Fei Wang, Zhao Zhen, Liu Chun, Zengqiang Mi, Bri-Mathias S. Hodge, M. Shafie‐khah, João P. S. Catalão. 2018

148 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/5ed812934c7513e4e9c0b141dbc5999c55b03e80

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

In Computer Vision and Pattern Recognition

1. M. Shafie‐khah
2. João P. S. Catalão
3. Fei Wang
4. José M. F. Moura
5. Aliaksei Sandryhaila
6. Vassilis Kalofolias

In Renewable Energy, Sustainability and the Environment

1. Neven Duic
2. João P. S. Catalão
3. Fei Wang

Citations in the corpus

• Generative adversarial networks and convolutional neural networks based weather classification model for day ahead short-term photovoltaic power forecasting (2019, background): “For example, demand response (DR) can shift electricity consumptions in DR event time to improve the flexibility of system operation [6], leverage the demand-side resources through a variety of electricity market mechanisms to balance the active power and enhance system reliability [7], participate ”