Modeling and aggregated control of large-scale 5G base stations and backup energy storage systems towards secondary frequency support

Abstract

A significant number of 5G base stations (gNBs) and their backup energy storage systems (BESSs) are redundantly configured, possessing surplus capacity during non-peak traffic hours. Moreover, traffic load profiles exhibit spatial variations across different areas. Proper scheduling of surplus capacity from gNBs and BESSs in different areas can provide sustainable frequency support for the power system without compromising the operation of 5G network. In this paper, a comprehensive strategy is proposed to safely incorporate gNBs and their BESSs (called “gNB systems”) into the secondary frequency control procedure. Initially, an aggregated model is developed using a state space method to capture the state of a cluster of heterogeneous gNB systems (gNBs-cluster). Subsequently, a utility function is defined to evaluate the quality of 5G network operation in a normalized manner. Based on this utility function, an aggregated control method is proposed, including real-time available power estimation and model predictive control (MPC) for the gNBs-cluster, which ensures the 5G network operation within the security constraint during demand response processes. Simulations, utilizing actual device data, demonstrate the effectiveness of the proposed method in improving power system frequency performance while guaranteeing the safety and reliability of the 5G network.