Medium and long-term electricity price forecasting in deregulated power markets is important to market operators and participants. Lack of access to detailed system information and uncertainty in changing market pressures including fuel price, generation additions and retirements, changes in demand, and transmission additions compound the difficulties of accurately predicting market dynamics. Increasing penetration of renewable resources can affect the market in unpredictable ways. We seek to develop a highly parallelizable production cost model capable of forecasting long-term price dynamics under a variety of market scenarios. Using this framework, uncertainty in inter- and intra-regional market dynamics can be quantified using Monte-Carlo simulation. The framework was tested using a reduced model of the ERCOT power market. Estimation methods were tested for generator heat rate and intra-regional wind capacity factor, and compared the results to historical LMP data for the year 2011. Areas for future improvement were identified for the wind capacity factor estimation method, as well as the model as a whole moving forward.