Impact of Weather Conditions on Renewable Energy Consumption

Nandanikar, Shivani Shrikant (2024) Impact of Weather Conditions on Renewable Energy Consumption. Masters thesis, Dublin, National College of Ireland.

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Abstract

The proposed study examines the impact of the weather conditions like temperature, pressure, humidity, rain, wind and solar energy on renewable energy consumption, focusing on studying the energy consumption patterns and impact of combination of complementary energy sources like solar and wind energy on energy consumption. Use of machine learning models along with performing the cross-validation on ML models such as Polynomial Regression, Random Forest, and Gradient Boosting, also time series analysis is being performed by using the combination of time series models like ARIMA, SARIMA + GARCH, and the multivariate VAR model, the research analyses energy consumption patterns over time. The key findings showed that amongst the applied three ML algorithms Random Forest outperformed with an 89% accuracy in predicting energy consumption based on weather variables like temperature, pressure, humidity, etc. The VAR model highlights the complementary relationship between solar and wind energy, which suggested a more stable energy supply when these two complementary energy sources are combined. This research provides significant insights into optimizing renewable energy consumption, which will help policymakers to create and develop sustainable energy strategies to reduce climate change impacts.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Mulwa, Catherine UNSPECIFIED
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HC Economic History and Conditions > Natural resources > Power resources > Energy consumption Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	25 Aug 2025 08:15
Last Modified:	25 Aug 2025 08:15
URI:	https://norma.ncirl.ie/id/eprint/8598

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