So, the distribution more looks like a normal distribution, but the error of linear model increase, I will continue to search but if you have other idea I'll take it.

Well it doesn't matter too much if the y-variable itself is normally distributed. You just need the assumptions about the model error term to hold. So you should be working to normalize them and get homoscedasticity!