The intercept and its lack of significance is not a problem. The significance is testing if the intercept is zero (Ho: $b_0$=0) which isn't a test you are likely to be very interested in. If you scaled and centered your data, the intercept should be very close to zero. I would recommend removing the intercept from the model since you are working with standardized data.
The picture below represents the effect of centering data which came from a somewhat similar question (link here). See that the intercept is forced to be zero:
And as stated in another similar question (see the answer by Joshua here):
Removing the intercept is a different model, but there are plenty of examples where it is legitimate.[...]The case of standardized data. In some cases, one may be working with standardized data. In this case, the intercept is 0 by design.
Finally, the qqplot does look appropriate. (however take a look at point 63)