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A new application of the Aggregation-Decomposition approach (AD) to the optimal scheduling of large hydrothermal generation systems with multiple reservoirs is presented. The problem (with N reservoirs) is decomposed into N subproblems with two state variables. Each subproblem finds the optimal operating policy for one of the reservoir as a function of the energy content of that reservoir and the aggregate energy content of the remaining reservoirs. The subproblems are solved by stochastic dynamic programming taking into account the detailed models of the hydro chains as well as the stochasticity and correlation of the hydro inflows. The method has been successfully implemented on a 10 reservoir hydrothermal power system.