Forecasting Residential Heating and Electricity Demand with Scalable, High-Resolution, Open-Source Models (opens in new tab)

arXiv:2505.22873v2 Announce Type: replace-cross Abstract: We present a novel framework for high-resolution forecasting of residential heating demand and non-heating electricity demand using probabilistic deep learning models. Because our models are trained on electricity consumption from a predominantly gas-heated region, the learned electricity demand patterns primarily reflect non-heating end uses such as lighting, appliances, and cooling. We focus specifically on providing hourly building-...