• Build an open source technology explicit energy economy optimization model. We provide public access to our revision control system via the web. We also plan to take snapshots of model source code and data used to produce published model-based analysis, enabling third party verification of our work.
  • Utilize open source software tools wherever possible. This includes the programming language, database, graphing and visualization tools, and solvers. This makes the TEMOA model broadly accessible. The biggest challenge is the choice of solvers: the best linear solvers (e.g. CPLEX and Gurobi) are commercial products.
  • Design the model to make uncertainty analysis more tractable. We plan to develop scripts that automate sensitivity analysis, Monte Carlo simulation, multi-stage stochastic optimization, and search techniques to find near-optimal alternative solutions.
  • Utilize multi-core and compute cluster environments to perform rigorous uncertainty analysis. Given the steep drop in computer hardware, running code in an embarrassingly parallel fashion to enable uncertainty analysis has become a practical and cost-effective option.