Proceedings of the International Conference on Sustainable Computing and Artificial Intelligence (ICSCAI 2025)

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Leveraging Weather Data and Machine Learning to Enhance Electricity Generation Efficiency

Authors
Aditya S. Mehta1, *
1Electrical Engineering Department, California State University, Los Angeles, USA
*Corresponding author. Email: Adityamehta92l4@gmai1.com
Corresponding Author
Aditya S. Mehta
Available Online 28 May 2026.
DOI
10.2991/978-94-6239-674-6_4How to use a DOI?
Keywords
Predictive modeling; Renewable energy; Power plant optimization; Sustainable energy; Demand forecasting
Abstract

Electricity generation is a complex and dynamic process that is sensitive to demand, calls often due to the weather. The present research paper aims to investigate the association of weather variables with electricity generation, which will, in turn, help improve the efficiency of power plants. We apply algorithms and develop models to predict how much energy will be generated based on the past energy generation numbers (both renewable and non-renewable) and related weather metrics (such as temperature, wind speed and cloud cover). Our results show how weather predictors can improve the forecasting of electricity needs to create a better-balanced system for electricity supply. According to the study, optimisation of the activities in generators contributes mitigations of energy loss in the transmission of energy. Also maximizes generation of effective capacity and supports the sustainability of energy.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainable Computing and Artificial Intelligence (ICSCAI 2025)
Series
Advances in Engineering Research
Publication Date
28 May 2026
ISBN
978-94-6239-674-6
ISSN
2352-5401
DOI
10.2991/978-94-6239-674-6_4How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Aditya S. Mehta
PY  - 2026
DA  - 2026/05/28
TI  - Leveraging Weather Data and Machine Learning to Enhance Electricity Generation Efficiency
BT  - Proceedings of the International Conference on Sustainable Computing and Artificial Intelligence (ICSCAI 2025)
PB  - Atlantis Press
SP  - 29
EP  - 38
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-674-6_4
DO  - 10.2991/978-94-6239-674-6_4
ID  - Mehta2026
ER  -