Big Data Analytics for Renewable Energy Optimization

This research project focuses on optimizing renewable energy systems using Big Data Analytics. The study analyses massive datasets generated from solar, wind, and smart grid sources to improve energy forecasting, demand prediction, and efficiency. Using data mining, machine learning models, and distributed processing frameworks like Hadoop and Spark, the system identifies patterns that enhance energy generation and reduce wastage. The project provides a scalable architecture for handling high-volume energy data and demonstrates how analytics-driven insights support sustainability and reliable energy distribution.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-15
DOI
https://doi.org/10.5281/zenodo.17617158
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Big Data Analytics for Renewable Energy Optimization

Zenodo (CERN European Organization for Nuclear Research)
Energy Load and Power Forecasting
article

Big Data Analytics for Renewable Energy Optimization

article en

Abstract

This research project focuses on optimizing renewable energy systems using Big Data Analytics. The study analyses massive datasets generated from solar, wind, and smart grid sources to improve energy forecasting, demand prediction, and efficiency. Using data mining, machine learning models, and distributed processing frameworks like Hadoop and Spark, the system identifies patterns that enhance energy generation and reduce wastage. The project provides a scalable architecture for handling high-volume energy data and demonstrates how analytics-driven insights support sustainability and reliable energy distribution.

Zenodo (CERN European Organization for Nuclear Research)
Koneru Lakshmaiah Education Foundation (IN)
Affordable and clean energy
Openalex Percentile: Top 48%
Energy Load and Power Forecasting
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