article · 2023

A Comparative Study of Forecasting Problems on Electrical Load Timeseries Data using Deep Learning Techniques

Battula Harish, Debasmita Panda, Krishna Reddy Konda, Ajay Soni

Cited by 6Abstract and details only

Abstract

This work presents a comparative study of forecasting problems on the Austria country electrical timeseries load demand data using deep learning models ANN-MLP, RNN-LSTM, and ID-CNN for short-term and medium-term electrical load forecast using different timestamps data and found that single timestamp ahead prediction (STAP) using MLP and multiple timestamps ahead prediction (MTAP) using ID-CNN show better results with reduced MAPE. ID-CNN is selected as the best model for both short-term 1-day ahead load forecast using 1-hour timestamp data with MTAP methodology resulting in MAPE 4.62% and for mid-term 1-year ahead load forecast using 1-month timestamp data with STAF methodology resulting in MAPE 1.45%.

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APA 7

Harish, B., Panda, D., Konda, K. R., & Soni, A. (2023). A Comparative Study of Forecasting Problems on Electrical Load Timeseries Data using Deep Learning Techniques. https://doi.org/10.1109/icps57144.2023.10142125

MLA 9

Harish, Battula, et al. “A Comparative Study of Forecasting Problems on Electrical Load Timeseries Data using Deep Learning Techniques.” 2023, pp. 1–5, https://doi.org/10.1109/icps57144.2023.10142125.

Chicago

Harish, Battula, Debasmita Panda, Krishna Reddy Konda, and Ajay Soni. 2023. “A Comparative Study of Forecasting Problems on Electrical Load Timeseries Data using Deep Learning Techniques.” https://doi.org/10.1109/icps57144.2023.10142125.

Harvard

Harish, B. et al. (2023) ‘A Comparative Study of Forecasting Problems on Electrical Load Timeseries Data using Deep Learning Techniques’. Available at: https://doi.org/10.1109/icps57144.2023.10142125.

BibTeX

@article{harish2023comparative,
  title = {{A Comparative Study of Forecasting Problems on Electrical Load Timeseries Data using Deep Learning Techniques}},
  author = {Harish, Battula and Panda, Debasmita and Konda, Krishna Reddy and Soni, Ajay},
  pages = {1--5},
  year = {2023},
  doi = {10.1109/icps57144.2023.10142125}
}

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A Comparative Study of Forecasting Problems on Electrical Load Timeseries Data using Deep Learning Techniques

Abstract

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