Aggregated Load Forecasting

Aggregated Load Forecasting is a type of load forecasting that predicts the collective electricity demand across multiple consumers, geographic areas, or load categories by integrating individual consumption patterns into a single, unified forecast, thereby enabling more stable and accurate predictions at a higher hierarchical level compared to individual-level forecasts.

65

Publications

3.9K

Citations

242

Authors

101

Institutions

Publications per year

2017–2026

39

Variants

Aggregate Load Forecasting

Authors

242

  1. RR
    Ram Rajagopal

    Stanford University, United States

    4 publications · 194 citations

    4

    h-index

  2. RS
    Raffi Sevlian

    Stanford University, United States

    4 publications · 194 citations

    4

    h-index

  3. YW
    Yi Wang

    Tsinghua University, China

    3 publications · 490 citations

    3

    h-index

  4. YW
    Yishen Wang

    Global Energy Interconnection Research Institute North America, United States

    2 publications · 54 citations

    2

    h-index

  5. YP
    Yayu Peng

    University of Nebraska–Lincoln, United States

    2 publications · 54 citations

    2

    h-index

1–5 of 242

Venues

  1. Applied Energy

    5 publications · 406 citations

    5

    h-index

  2. Energies

    5 publications · 212 citations

    5

    h-index

  3. IEEE Transactions on Smart Grid

    4 publications · 618 citations

    4

    h-index

  4. IEEE Transactions on Industry Applications

    3 publications · 319 citations

    3

    h-index

  5. Electric Power Systems Research

    3 publications · 77 citations

    3

    h-index

1–5