I have started working with optimization models to minimize the total generation costs of electricity in a system. The basic idea in this model is to minimize the overall system cost given a certain level of demand. I want to use this model to forecast costs in the future, which means that I have to make some assumptions about the demand and how it will increase or decrease. The problem is that this is a typical chicken-and-egg situation. If I assume an increase in demand, the system cost will be higher, thereby reducing the demand.
With time series data, this problem can be addressed using a lagged variable. So, I was wondering if there is a way to apply this concept to optimization models. How would you approach this problem? Can you recommend some articles or books addressing this issue?