Physical Forecasting Models

Physical Forecasting Models is a forecasting methodology that belongs to the class of renewable generation prediction techniques and is distinguished by its reliance on first-principles physical laws and numerical weather prediction to simulate atmospheric and energy conversion processes for estimating future power output.

171

Publications

14K

Citations

628

Authors

303

Institutions

Publications per year

2017–2026

107

Variants

Physical Forecasting

Authors

628

  1. MJ
    Martin János Mayer

    Budapest University of Technology and Economics, Hungary

    4 publications · 731 citations

    4

    h-index

  2. LL
    Lars Landberg

    Technical University of Denmark, Denmark

    3 publications · 439 citations

    3

    h-index

  3. MP
    Marius Paulescu

    West University of Timişoara, Romania

    3 publications · 360 citations

    3

    h-index

  4. VB
    Viorel Bădescu

    Universitatea Națională de Știință și Tehnologie Politehnica București, Romania

    3 publications · 360 citations

    3

    h-index

  5. TO
    Takashi Oozeki

    National Institute of Advanced Industrial Science and Technology, Japan

    3 publications · 69 citations

    3

    h-index

1–5 of 628

Venues

  1. Solar Energy

    20 publications · 1.6K citations

    18

    h-index

  2. Energy

    12 publications · 1K citations

    12

    h-index

  3. Energy Conversion and Management

    8 publications · 1.2K citations

    8

    h-index

  4. Renewable Energy

    9 publications · 717 citations

    8

    h-index

  5. Energies

    5 publications · 262 citations

    5

    h-index

1–5