Temporal and Spatial Optimization for 5G Base Station Groups in Distribution Networks

Abstract

With the large-scale connection of 5G base stations (BSs) to the distribution networks (DNs), 5G BSs are utilized as flexible loads to participate in the peak load regulation, where the BSs can be divided into base station groups (BSGs) to realize inter-district energy transfer. A Stackelberg game-based optimization framework is proposed, where the distribution network operator (DNO) works as a leader with dynamic pricing for multi-BSGs; while BSGs serve as followers with the ability of demand response to adjust their charging and discharging strategies in temporal dimension and load migration strategy in spatial dimension. Subsequently, the presence and uniqueness of the Stackelberg equilibrium (SE) are provided. Moreover, differential evolution is adopted to reach the SE and the optimization problem in multi-BSGs is decomposed to solve the time-space coupling. Finally, through simulation of a practical system, the results show that the DNO operation profit is increased via cutting down the peak load and the operation costs for multi-BSGs are reduced, which reaches a win-win effect.