  In this paper, we investigate the problem of minimizing the sum of energy
cost and thermal discomfort cost in a long-term time horizon for a sustainable
smart home with a Heating, Ventilation, and Air Conditioning (HVAC) load.
Specifically, we first formulate a stochastic program to minimize the time
average expected total cost with the consideration of uncertainties in
electricity price, outdoor temperature, renewable generation output, electrical
demand, the most comfortable temperature level, and home occupancy state. Then,
we propose an online energy management algorithm based on the framework of
Lyapunov optimization techniques without the need to predict any system
parameters. The key idea of the proposed algorithm is to construct and
stabilize four queues associated with indoor temperature, electric vehicle
charging, and energy storage. Moreover, we theoretically analyze the
feasibility and performance guarantee of the proposed algorithm. Extensive
simulations based on real-world traces show the effectiveness of the proposed
algorithm.
