Long-term power system expansion planning by dynamic programming and production cost simulation

This paper extends previously published results on the application of a dynamic programming optimization approach to the planning of systems, with special emphasis on the long-term expansion of power systems. Future uncertainties about loads, equipment costs, etc. are considered explicitly in the method described. A practical computational solution to the resulting stochastic optimization is obtained by means of the recently developed open-loop feedback approximation. Further, it is shown how various known approaches of production cost simulation can be used in conjunction with the dynamic programming optimization to accommodate large systems that may be represented with great technical detail.