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In this paper we propose distributed load management in smart grid infrastructures to control the power demand at peak hours, by means of dynamic pricing strategies. The distributed solution that we propose is based on a network congestion game, which can be demonstrated to converge in a finite number of steps to a pure Nash equilibrium solution. We take advantage of the remarkable property of congestion games, according to which they are equivalent to potential games. We define a potential function characterized by a meaningful physical interpretation, so that we obtain the favorable result that the optimal local solution of each selfish consumer is also the solution of a global objective. We evaluate this approach for managing both the demand and the grid load and we show that load control can be effectively achieved implementing a distributed solution, which significantly reduce the signaling burden over the network.