In dynare,
The deterministic model means perfect foresight, and the shocks are set with exact value;
The stochastic model means imperfect foresight, and the shocks are set with its variance.

I have built a stochastic model (RBC), and I have calibrated the parameters and the realized values of TFP shocks from historical Marco data. Now I want to introduce the realized values of TFP shocks into my stochastic model to see how the business cycle it generates would differ from the reality.

After reading the whole UserGuide, I still cant find the solution……if I choose stochastic model in dynare, I can only introduce the variance of shocks. if I choose deterministic model in dynare, the shocks will be perfect foreseen so it will not be in line with my model…

You could take a look at this post and I think it would be helpful for your problem

(P.S. I would probably call it rational expectation rather than imperfect foresight, and stochastic model rather than random model, just terminology… sounds a little weird to me.)