How to go about cooling load forecast for a district level dataset?

I am trying to build a high accuracy cooling load forecast for a district-level dataset over various time horizons. My data consists of a time series of cooling load and consecutive weather data. I added a bunch of other features such as an hour of the day, day of the week, holiday or not, etc. My question is, what are some current models for the prediction of the time series load dataset like mine? I gather LSTM is the way to go. However, given the features I have identified, are there other models that are more accurate for such a forecast? If I chose to go the NN fitting route, what are some other features I can add?