Energy Cost Reduction for Hybrid Energy Supply Base Stations with Sleep Mode Techniques

Abstract

In this paper, we study an energy cost minimization problem in cellular networks, where base stations (BSs) are supplied with hybrid energy sources including harvested recyclable energy (RE), external power grids (PGs), distributed local generators (LGs) and power storages, and operate with sleep mode techniques. We formulate the problem into an optimization programming to achieve optimal decisions for energy scheduling and sleep control. To avoid frequent switching, we implement BS sleep mode techniques on a larger timescale by adopting a two-timescale approach. Based on the Lyapunov technique, we further propose a close-to-optimal algorithm which only requires mean price of PG energy in each time frame instead of future information about stochastic inputs (e.g., the amount of RE harvesting and user demand for data traffic). The proposed algorithm can achieve approximately minimal energy cost and ensure the stability of workload and battery virtual queues. We present theoretical analysis as well as numerical simulations to demonstrate the performance of the proposed algorithm. The results present the stability of queues and the reduction in system cost.