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The paper addresses the problem of decentralized optimization for a power system partitioned into several areas controlled by different transmission system operators (TSOs). The optimization variables are the settings for taps, generators' voltages and compensators', and the objective function is either based on the minimization of reactive power support, the minimization of active power losses, or a combination of both criteria. We suppose that each TSO assumes an external network equivalent for its neighboring areas and optimizes without concern for the neighboring systems' objectives its own optimization function. We study, in the context where every TSO adopts the same type of objective function, the performance of an iterative scheme, where every TSO refreshes at each iteration the parameters of its external network equivalents depending on its past internal observations, solves its local optimization problem, and then, applies its ldquooptimal actionsrdquo to the power system. In the context of voltage optimization, we find out that this decentralized control scheme can converge to nearly optimal global performance for relatively simple equivalents and simple procedures for fitting their parameters.