Smart Grids: AI-Enabled Energy Management and Demand Forecasting

The application of the Smart Grids with Artificial intelligence - AI has transformed the sector of management and demand forecasting dramatically. The objective of such research is to develop AI based prospective energy management system which involves advanced tool as LSTM for demand forecasting. The figure of merit stressed over the research in the literature has been data preprocessing, feature selection and classification techniques performed for improving the model performance. In order to provide an evidence of the success of this method in analyzing real time energy data, this is a case study of the use of Scikit Learn library. So, removing missing value, normalising the data, feature selection with RFE, classification with GBM. With the help of AI technology, the results suggest better accuracy of prediction and scalability, and is thus deemed a future of smart grid management.

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Publication Details

Published
2025-03-27
DOI
https://doi.org/10.1109/icfts62006.2025.11031861
Citations
2
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
1.46
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Smart Grids: AI-Enabled Energy Management and Demand Forecasting

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article en
2 citations

Abstract

The application of the Smart Grids with Artificial intelligence - AI has transformed the sector of management and demand forecasting dramatically. The objective of such research is to develop AI based prospective energy management system which involves advanced tool as LSTM for demand forecasting. The figure of merit stressed over the research in the literature has been data preprocessing, feature selection and classification techniques performed for improving the model performance. In order to provide an evidence of the success of this method in analyzing real time energy data, this is a case study of the use of Scikit Learn library. So, removing missing value, normalising the data, feature selection with RFE, classification with GBM. With the help of AI technology, the results suggest better accuracy of prediction and scalability, and is thus deemed a future of smart grid management.

Thi Qar University (IQ), IILM Institute for Higher Education (IN), PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN), Graphic Era University (IN), Saveetha University (IN)
Affordable and clean energy
Openalex Percentile: Top 17%
Energy Load and Power Forecasting
1.46
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