Gas consumption outliers detection - Neural network project. Bad results
Just an idea - your data is highly seasonal: daily and weekly cycles are quite perceptible. So first of all, try to decompose your variables (gas and electricity consumption, temperature, and solar radiation). Here is a nice tutorial on time series decomposition for R. 

After obtaining trend and seasonal components, the most interesting part begins. It's just an assumption, but I think, gas and electricity consumption variables would be quite predictable by means of time series analysis (e.g., ARIMA model). From my point of view, the most exiting part here is to try to predict residuals after decomposition, using available data (temperature anomalies, solar radiation, wind speed). I suppose, these residuals would be outliers, you are looking for. Hope, you will find this useful.