Enhanced Deep Learning Based Predictive Analysis of Electricity Power Consumption Forecasting for Maharashtra State Electricity Distribution Company Ltd. (MSEDCL)

Authors

  • Kanchan A. Khedikar ,Dr.Piyush Kumar Pareek

Keywords:

electricity power consumption forecasting, Gated Recurrent Unit, Long Short-Term Memory, prophet, prediction analysis, sustainable energy planning, MSEDCL

Abstract

Accurate forecasting of electricity power consumption is vital for efficient grid operation, optimal resourcemanagement, and sustainable energy planning. Energy consumption analysis involves gathering, evaluating, and interpretingdata on energy usage—particularly electricity. Our research centers on forecasting energy demand for Maharashtra StateElectricity Distribution

References

Dmitry Brykin, (2024). Sales Forecasting Models: Comparison between ARIMA, LSTM and Prophet. Journal of Computer

Science, 20(10) 1222-1230, DOI: 10.3844/jcssp.2024.1222.1230, (2024)

Rashmi Bareth, Matushree Kochar, Anamika Yadav, Mohammad Pazoki, “Load Forecasting Model Using LSTM for

Indian State Load Dispatch Centre”, in Electrica 2024, DOI: 10.5152/electrica.2024.23158, August 2024,

https://electricajournal.org/Content/files/sayilar/85/ELECT_20 230158-AOP-1508(1).pdf

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Published

2024-06-20

How to Cite

Kanchan A. Khedikar ,Dr.Piyush Kumar Pareek. (2024). Enhanced Deep Learning Based Predictive Analysis of Electricity Power Consumption Forecasting for Maharashtra State Electricity Distribution Company Ltd. (MSEDCL) . Journal of Computational Analysis and Applications (JoCAAA), 33(4), 907–914. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3740

Issue

Vol. 33 No. 4 (2024): Selected Papers on Computational Techniques Across Multidisciplinary Fields: Innovations and Applications

Section

Articles

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