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Predicting Short Term Energy Demand in Smart Grid: A Deep Learning Approach for Integrating Renewable Energy Sources in Line with SDGs 7, 9, and 13. (arXiv:2304.03997v2 [cs.LG] UPDATED)
cs.LG updates on arXiv.org arxiv.org
The integration of renewable energy sources into the power grid is becoming
increasingly important as the world moves towards a more sustainable energy
future in line with SDG 7. However, the intermittent nature of renewable energy
sources can make it challenging to manage the power grid and ensure a stable
supply of electricity, which is crucial for achieving SDG 9. In this paper, we
propose a deep learning-based approach for predicting energy demand in a smart
power grid, which can …
arxiv deep learning demand electricity energy future grid integration intermittent line nature paper power renewable smart world