@inproceedings{scholars15434,
            note = {cited By 3; Conference of 3rd IEEE International Conference on Electrical, Control and Instrumentation engineering, ICECIE 2021 ; Conference Date: 27 November 2021 Through 28 November 2021; Conference Code:176202},
             doi = {10.1109/ICECIE52348.2021.9664713},
            year = {2021},
           title = {Implication of Diverse Modalities for Electrical Load Forecasting},
         journal = {ICECIE 2021 - 2021 International Conference on Electrical, Control and Instrumentation Engineering, Conference Proceedings},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
            isbn = {9781665449663},
          author = {Azeem, A. and Ismail, I. and Jameel, S. M. and Harindran, V. R.},
        abstract = {The extensive research and development over aeras have proposed numerous techniques for load forecasting (L.F). The major targeted area was either the grid, commercial or residential consumers but the industrial sector was not widely explored; specially the spaciousness of the grid isolated industries or independent power plants (IPP's). The paper intent to investigates the L.F methods and highlight their flaws, comprehensive review of their limitations and existing potential challenges to associated with electrical L.F. The study furthers three potential research questions and respective objectives attained after extensive quality assessment criteria for inclusion or exclusion of literature. However, in electrical load forecasting, the choice of parameters and model selection criteria leads to an optimization challenge. The methods proposed with trial and error combined with expert knowledge to optimize the input parameters have been widely used in past. Such custom-made approaches are difficult to be considered in the isolated industries or IPP's due to their nature of operations. Also, the renewable energy integration with conventional grids has commended towards more precise and accurate L.F. This paper presents a comprehensive review of forecasting techniques for electrical load forecasting and examine the models. Additionally, the research gaps are also discussed. {\^A}{\copyright} 2021 IEEE.},
        keywords = {Electric load forecasting; Electric power plant loads; Industrial plants; Smart city; Smart power grids, Diverse modality; Electrical load forecasting; Grid-isolated power plant; Independent power plants; Industrial power plants; Isolated power; Load forecasting; Research and development; Residential consumers; Smart grid, Electric power transmission networks},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124700275&doi=10.1109\%2fICECIE52348.2021.9664713&partnerID=40&md5=6888b9c2f361bd3d3b5c2c7bbdf8fe36}
}