Forecasting of climatic influence on energy generation from renewable resources in Spain using Neural Network Models

Kallumpuram Prabhakaran, Aiswarya (2024) Forecasting of climatic influence on energy generation from renewable resources in Spain using Neural Network Models. Masters thesis, Dublin, National College of Ireland.

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Abstract

The technological advancement and population growth has brought significant impact in the need for electricity throughout the world. The soar in energy demand brought significant impact on environment due to the over usage of conventional methods such as fossil fuels. The combustion of natural gases, coal and oil is releasing considerable amount of CO2 into the atmosphere which highly dangerous to our planet. This can be solved by switching from this traditional method to renewable resources such as solar, wind, biomass etc. which are naturally available in nature in sufficient amount. But their dependency on the weather is a challenging factor. This study is addressing this issue by forecasting the energy generation from renewable resources under the influence of weather. For conducting this, the study employs the advanced neural network models such as LSTM, Stacked LSTM, LSTM-CNN and LSTNet to forecast the impact of weather on renewable energy production. The comparison of results shows, LSTNet’s superior performance with 98.99% accuracy over the other models, which is evaluated based on the evaluation metrics such as mean squared error, means absolute error, root mean squared error and r- squared value. The outcomes emphasize the importance of the selection of appropriate predicting models and also showcase LSTNet as a valuable tool for future energy predictions.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Shahid, Abdul UNSPECIFIED
Uncontrolled Keywords:	Weather; Renewable Resources; Neural network models; LSTNet
Subjects:	D History General and Old World > DP Spain 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 T Technology > TD Environmental technology. Sanitary engineering
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	09 May 2025 14:15
Last Modified:	09 May 2025 14:15
URI:	https://norma.ncirl.ie/id/eprint/7540

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