I am predicting electricity usage for customers which is highly skewed. Regular regression models did not fit well due to skewed distribution, hence I tried quantile regression. I'm obtaining the models for 0.1, 05 and 0.9 quantiles. So I have 3 set of predictions for the three models optimized at the quantiles specified above. All the three models perform very well for the quantiles optimized but the performance decreases for other quantiles as one would expect. Regular averaging would give equal weights to all three model outputs and hence does not represent true distribution. Can anyone suggest what would be the best method for model averaging for quantile regression method?