  The year of 2020 has witnessed the unprecedented development of 5G networks,
along with the widespread deployment of 5G base stations (BSs). Nevertheless,
the enormous energy consumption of BSs and the incurred huge energy cost have
become significant concerns for the mobile operators. As the continuous decline
of the renewable energy cost, equipping the power-hungry BSs with renewable
energy generators could be a sustainable solution. In this work, we propose an
energy storage aided reconfigurable renewable energy supply solution for the
BS, which could supply clean energy to the BS and store surplus energy for
backup usage. Specifically, to flexibly reconfigure the battery's
discharging/charging operations, we propose a deep reinforcement learning based
reconfiguring policy, which can adapt to the dynamical renewable energy
generations as well as the varying power demands. Our experiments using the
real-world data on renewable energy generations and power demands demonstrate
that, our reconfigurable power supply solution can achieve an energy saving
ratio of 74.8%, compared to the case with traditional power grid supply.

Distributed, Parallel, and Cluster Computing