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Sleep modes are one of the most widely investigated techniques to decrease energy consumption in cellular access networks. However, the application of such algorithms on present day base stations (BS) equipment poses several challenges. Indeed, currently installed BSs are unfit for frequent on/off cycles. This may lead to increased failure rates and malfunctioning, ultimately resulting in significant CAPEX and OPEX increases for mobile network operators (MNOs). This situation calls for a new generation of flexible BSs endowed with a ”hot standby” mode, which guarantees quick activation times without affecting BS availability. However, when such new BS models become available, MNOs will need to determine a migration path to a new network deployment with progressive replacement of old BS equipment. In this paper, we propose an approach to quantify the benefits achievable by MNOs with the deployment of flexible BSs, in terms of maximum energy efficiency achievable with a given fraction of flexible BSs in their network. More specifically, we propose a method for estimating, for a given percentage of flexible BSs, the energy optimal density of static and flexible BSs, which is sufficient to serve a given set of active users with predefined performance guarantees. We show how to apply our method to derive bounds on the maximum energy savings achievable through sleep modes, as a function of the fraction of flexible BSs. We determine the effect of uncertainty in traffic predictions on sleep modes performance, and we derive indications for optimal network planning strategies.