A Dynamic Programming Model for the Expansion of Electric Power Systems

This paper describes a dynamic programming model that has been developed to determine an optimal expansion plan for the generating capacity of an electric power system. The optimization model determines the least-cost mix of capacity between hydro, nuclear, thermal and peaking turbine plants, the size of the plants to add to the system, and the timing of these additions. We show how the computational requirements of this four-state-variable, four-decision-variable problem can be substantially reduced, resulting in a computationally feasible model. The techniques developed are applicable to a large class of capital budgeting problems under uncertainty. Reference is also made to the actual application of the model and an example is presented.