Resilience enhancement strategies for distribution networks considering the coordination of 5G base stations and multiple flexible resources

Abstract

In recent years, the increasing frequency of extreme natural disasters has significantly exposed the vulnerability of distribution networks. To address this challenge, this study proposes a resilience enhancement strategy that integrates 5G base stations with multiple flexible resources. First, a disaster scenario modeling framework is developed by considering typhoon wind speed, line outage probability, and renewable generation curtailment, and representative scenarios are extracted using Latin Hypercube Sampling (LHS) and K-means++ clustering. Subsequently, a coordinated optimization model is established with the objectives of minimizing critical load loss and economic cost, in which the energy storage of 5G base stations is utilized not only to guarantee communication loads but also to participate in system dispatch. Meanwhile, distributed generation, electric vehicles, and mobile energy storage systems are coordinately scheduled, combined with network reconfiguration to achieve complementary utilization of multiple resources. The bi-objective problem is then reformulated into a mixed-integer second-order cone programming (MISOCP) model using second-order cone relaxation and the weighted-sum method, and efficiently solved. Finally, case studies conducted on a modified IEEE 33-bus system demonstrate that, compared with uncoordinated operation under extreme disaster conditions, the proposed strategy reduces critical load loss by 84.6%, decreases economic losses by 76.9%, and improves the comprehensive objective value by 83.7%. Furthermore, by coordinating 5G base stations with mobile energy storage to support islanded areas, the overall comprehensive objective is further improved by 89.1%.