Deep learning techniques for load forecasting in large commercial buildings by using Data during Pandemic COVID-19

This study tackles the issue of accurately forecasting energy consumption during the COVID-19 pandemic. Through the development of advanced forecasting models for energy usage in buildings, the research aims to establish adaptable frameworks for future crises and similar scenarios. The results emphasize notable decreases in energy consumption during periods of lockdown, especially in the commercial and industrial sectors. With the enhancement in prediction accuracy, the proposed models provide valuable insights for efficient energy management. This research has a scientific contribution by improving the adaptability of power systems to changing demands and ensuring more reliable energy management in crises.