LAUSR

The operations of base stations (BSs) contribute most of the energy consumption in the cellular wireless networks. Powering BSs by distributed energy resources (DER) such as photovoltaic (PV) and energy storage is an effective way to reduce on-grid power consumption and build green wireless networks. Optimal energy management of BSs helps to reduce electricity bills for the wireless network and provides flexibility to the power networks. This paper proposes the concept of spatial-temporal energy management (ST-EM) for the energy management of BSs. On the one hand, the BSs manage their power consumption according to the real-time prices; on the other hand, the BSs adjust the user associations and change their power consumption according to the price differences among different BSs. The ST-EM of BSs is formulated as a large-scale mixed-integer nonlinear programming (MINLP) problem, which is proven to be NP-hard. We propose a heuristic approach to search for one sub-optimal solution by decomposing the original problem into an energy network optimization sub-problem and a communication network optimization sub-problem. The two sub-problems are solved alternatively until convergence. Numerical experiments are conducted to verify the effectiveness of our proposed method.