The objective of this paper is to present a new methodology for the solution of hydrothermal systems expansion planning problems that takes into account uncertainties of future water inflows to the system reservoirs. The problem consists on the determination of a set of hydroeletric and thermoelectric plants that will be constructed in order to minimize the sum of investiment costs and expected operation costs during the planning period. The expansion problem can be solved by decomposition techniques in which the problem in divided into a master problem that contains the investiment variables and many subproblems that contain the operation variables. The master problem can be solved by linear or integer/linear programming recursion. In this paper, since the system reservoirs are individually represented, Stochastic Dual Dynamic Programming techniques will be applied in order to avoid the "curse of dimensionality" of dynamic programming. The fundamental objective of the study is to investigate efficient coordination mechanisms between master problem and operation subproblems that lead to a global optimization of power systems expansion planning problem.