Differentiable physics: the forecast engine

The summary of this theme is in progress. The differentiable-physics series builds models from physical terms (demand, heating, solar) whose parameters are fitted by gradient descent. This theme covers whether such a model, driven by ECMWF ensemble weather forecasts, forecasts Primary substation demand up to 7 days ahead as well as the production recipe does, on its own or as the starting point of the production recipe's XGBoost model. The Experiments page lists every experiment tried, with its verdict and a take-home message, and the Research plan lists what is planned next.