%0 Conference Paper
%A Azeem, A.
%A Ismail, I.
%A Jameel, S.M.
%A Romlie, F.
%A Danyaro, K.U.
%D 2022
%F scholars:17263
%I Institute of Electrical and Electronics Engineers Inc.
%K Decision making; Electric power plant loads; Forecasting; Smart city, Concept drifts; Data stream; Different generation modality; Dynamic forecasting; Electrical energy; Electrical load forecasting; Load forecasting; Load forecasting model; Online data; Smart grid, Smart power grids
%P 18-22
%R 10.1109/ICFTSC57269.2022.10039888
%T Concept Drift Scenarios in Electrical Load Forecasting with Different Generation Modalities
%U https://khub.utp.edu.my/scholars/17263/
%X The electrical energy is basic necessity for daily operations. Therefore, its efficient and intelligent management is required. However, the utilities require rapid and efficient decision-making which depends on efficient load forecasting models. The existing load forecasting models stand obsolete in the dynamic environments, where rapid decisions are required; based on online data streams. The online data streams in electrical environment comprise of different generation modalities and consist of different variations (concept drift) in pattern, parameter, and modalities. Therefore, this study explores the possible concept drift scenarios in electrical load forecasting with different generation modalities and provide a framework to resolve the issue. © 2022 IEEE.
%Z cited By 0; Conference of 2022 International Conference on Future Trends in Smart Communities, ICFTSC 2022 ; Conference Date: 1 December 2022 Through 2 December 2022; Conference Code:186671