Let's discuss what a PFE is before looking at the equation.
PFE is a common statistical measure for the amount of money you'll lose if your counterparty defaults. Let's give an example, say if you were to long 1000 far-in-the-money call options with a bank. Those options worth a lot to you because they're all in-the-money, it's something that you want to exercise upon maturity. However, what if the bank defaults (assume zero recovery)? You'd lose everything! In this example, your future exposure would be the value of your options, discounted back to today.
Now, what if you were to short those 1000 call options? Your portfolio would be negative. Now if the bank defaulted, you shouldn't be unhappy because you weren't supposed to get anything from the bank anyway. In credit risk, we say there is
Thus, counterparty exposure can be defined mathematically as:
max(x, 0). We'll also need a probability distribution for the future.
f(x) in your equitation defines the probability distribution. The integration gives you the average. You can think of the equation like: "average all the possible future exposure".
PFE is indeed commonly estimated by Monte-Carlo methods. How it's simulated depends on what it's simulated. For example, if I'm interested in how the interest rate would affect my portfolio. I would simulate the interest rates (eg: LIBOR) by modelling the change in basis points. I would set the time horizon to say, 2 years. Too short horizon would give unrealistic PFE as the default probability is usually quite low. Then I would take the 95% quartile of the simulated distribution as my PFE.
You should read this book to learn more. I've personally read it and I've found it very useful for understanding credit risks.