Load Forecasting Uncertainty Quantification

Load Forecasting Uncertainty Quantification is a methodological framework within load forecasting that characterizes the probabilistic bounds and confidence levels of predicted electricity demand by systematically assessing sources of uncertainty in forecasting models, inputs, and external factors.

220

Publications

14.9K

Citations

706

Authors

298

Institutions

Publications per year

2017–2026

121

Authors

706

  1. YW
    Yi Wang

    Tsinghua University, China

    10 publications · 1.2K citations

    10

    h-index

  2. NZ
    Ning Zhang

    Tsinghua University, China

    7 publications · 836 citations

    7

    h-index

  3. TH
    Tao Hong

    University of North Carolina at Charlotte, United States

    7 publications · 962 citations

    7

    h-index

  4. DS
    Dipti Srinivasan

    National University of Singapore, Singapore

    6 publications · 1.3K citations

    6

    h-index

  5. HQ
    Hao Quan

    National University of Singapore, Singapore

    5 publications · 1.1K citations

    5

    h-index

1–5 of 706

Venues

  1. Energy

    22 publications · 1.9K citations

    18

    h-index

  2. IEEE Transactions on Smart Grid

    17 publications · 1.9K citations

    16

    h-index

  3. Applied Energy

    13 publications · 904 citations

    13

    h-index

  4. IEEE Transactions on Power Systems

    14 publications · 2K citations

    13

    h-index

  5. International Journal of Forecasting

    12 publications · 821 citations

    12

    h-index

1–5