Joint probabilistic forecasting of electricity and heat demand in residential buildings using LSTM and weather-driven features
Forecasting energy demand is critical to resource optimization, grid operation, and sustainability for smart buildings and urban energy systems. This study presents a probabilistic forecasting framework designed to jointly predict hourly electricity and heat demand for a residential building using deep learning. The...