Renewable Energy Forecasting

Renewable Energy Forecasting is a systematic predictive methodology that estimates future power generation from renewable sources, such as solar and wind, by analyzing meteorological, historical, and operational data to address the inherent variability and uncertainty in renewable energy production within smart grid systems.

3.9K

Publications

230K

Citations

9.9K

Authors

2.5K

Institutions

Publications per year

2017–2026

2.8K

Authors

9.9K

  1. GK
    Georges Kariniotakis

    Centre Procédés, Energies Renouvelables et Systèmes Energétiques, France

    39 publications · 3.1K citations

    25

    h-index

  2. PP
    Pierre Pinson

    Technical University of Denmark, Denmark

    32 publications · 3.9K citations

    22

    h-index

  3. SL
    Sonia Leva

    Politecnico di Milano, Italy

    25 publications · 2.1K citations

    20

    h-index

  4. FW
    Fei Wang

    North China Electric Power University, China

    22 publications · 2.9K citations

    20

    h-index

  5. BH
    Bri‐Mathias Hodge

    National Laboratory of the Rockies, United States

    21 publications · 2.1K citations

    19

    h-index

1–5 of 9.9K

Venues

  1. Energy

    186 publications · 16.2K citations

    73

    h-index

  2. Renewable Energy

    160 publications · 15K citations

    69

    h-index

  3. Applied Energy

    138 publications · 13.9K citations

    67

    h-index

  4. IEEE Transactions on Sustainable Energy

    TSTE · 99 publications · 9.6K citations

    57

    h-index

  5. Energies

    250 publications · 11.7K citations

    54

    h-index

1–5