Supporting Decarbonization Through Energy Demand Forecasting with Climate Projections and Renewable Energy Integration

Given the increasing need to address climate change and ensure energy reliability, integrating renewable energy sources and climate projections into net energy demand forecasts is essential. Accurately forecasting net energy demand is critical for managing the electric grid and supporting decarbonization efforts, particularly in regions with a high penetration of renewable energy resources. This study focuses on the Northeast United States using historical data on energy demand, solar, and wind generation, and ERA5 atmospheric reanalysis data, while also integrating projections for future climate, solar, and wind energy. Using advanced deep learning models, we forecasted future net energy demand and evaluated the accuracy of these models with standard error metrics. Our findings highlight the critical role of integrated forecasting approaches in developing resilient, balanced, and sustainable energy systems. By addressing both current and future energy needs while effectively mitigating environmental impacts and climate related challenges, this research provides actionable insights for stakeholders and policymakers aiming to enhancing grid management and support comprehensive decarbonization strategies.