  In the emerging hybrid electricity market, mobile network operators (MNOs) of
cellular networks can make day-ahead energy purchase commitments at low prices
and real-time flexible energy purchase at high prices. To minimize electricity
bills, it is essential for MNOs to jointly optimize the day-ahead and real-time
energy purchase based on their time-varying wireless traffic load. In this
paper, we consider two different MNOs coexisting in the same area, and exploit
their collaboration in both energy purchase and wireless load sharing for
energy cost saving. Specifically, we propose a new approach named energy group
buying with load sharing, in which the two MNOs are aggregated as a single
group to make the day-ahead and real-time energy purchase, and their base
stations (BSs) share the wireless traffic to maximally turn lightly-loaded BSs
into sleep mode. When the two MNOs belong to the same entity and aim to
minimize their total energy cost, we use the two-stage stochastic programming
to obtain the optimal day-ahead and real-time energy group buying jointly with
wireless load sharing. When the two MNOs belong to different entities and are
self-interested in minimizing their individual energy costs, we propose a novel
repeated Nash bargaining scheme for them to negotiate and share their energy
costs under energy group buying and load sharing. Our proposed repeated Nash
bargaining scheme is shown to achieve Pareto-optimal and fair energy cost
reductions for both MNOs.
