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A system-level dynamic power management (DPM) strategy is presented to conserve energy of base stations in wireless access networks. It dynamically changes the operation state of multiple frequency carriers with the fluctuation of workloads to guarantee the QoS with minimum power consumption. First, an event-driven continuous-time Markov control processes model is introduced to formulate the DPM problem as a constrained optimization problem. Then, a policy iteration based reinforcement learning algorithm that combines potentials estimation and stochastic approximation is proposed for optimizing the DPM policy online. Simulation results demonstrate the effectiveness of the presented approach.