  Owing to the fluctuant renewable generation and power demand, the energy
surplus or deficit in each nanogrid is embodied differently across time. To
stimulate local renewable energy consumption and minimize the long-term energy
cost, some issues still remain to be explored: when and how the energy demand
and bidirectional trading prices are scheduled considering personal comfort
preferences and environmental factors. For this purpose, the demand response
and two-way pricing problems concurrently for nanogrids and a public monitoring
entity (PME) are studied with exploiting the large potential thermal elastic
ability of heating, ventilation and air-conditioning (HVAC) units. Different
from nanogrids, in terms of minimizing time-average costs, PME aims to set
reasonable prices and optimize profits by trading with nanogrids and the main
grid bi-directionally. In particular, such bilevel energy management problem is
formulated as a stochastic form in a long-term horizon. Since there are
uncertain system parameters, time-coupled queue constraints and the interplay
of bilevel decision-making, it is challenging to solve the formulated problems.
To this end, we derive a form of relaxation based on Lyapunov optimization
technique to make the energy management problem tractable without forecasting
the related system parameters. The transaction between nanogrids and PME is
captured by a one-leader and multi-follower Stackelberg game framework. Then,
theoretical analysis of the existence and uniqueness of Stackelberg equilibrium
(SE) is developed based on the proposed game property. Following that, we
devise an optimization algorithm to reach the SE with less information
exchange. Numerical experiments validate the effectiveness of the proposed
approach.
