光储式5G通信基站集群灵活性聚合与协同调度策略

Flexible aggregation and coordinated scheduling strategy for renewable powered 5G communication base station clusters

5G通信基站通常配备光储,数量庞大、功耗可调,是一种优质的电力灵活性调节资源。提出了多类型光储式5G基站集群灵活性资源聚合方法以及参与电网调峰的协同调度策略。首先,分析休眠机制下多类型基站功耗可调特性与计及基站备用电量的储能调节能力。基于极限场景思想,构建了光储式5G基站的灵活性空间量化模型。在此基础上,利用闵可夫斯基和法刻画异构基站柔性资源的时空耦合能量轨迹,得到海量基站集群的灵活性资源聚合可调域。其次,建立了基站集群聚合资源参与电能量市场和辅助服务市场的协同调度优化模型,提出了基于交替方向乘子法(alternating direction method of multipliers, ADMM)的分层分布式基站集群协同优化调度策略,将大规模基站集群调度问题降维分解为统一协同调峰功率响应、聚合功率自治调度和基站集群功率分配3个子问题进行求解。通过算例对比分析可知,所提策略可降低通信基站69.86%的用能成本,为提升通信资源利用率和电力系统灵活调节能力提供了有效手段。

5G communication base stations are numerous and usually equipped with photovoltaic and energy storage and their power consumption is adjustable.It is a high-quality resource for flexible power regulation.This paper proposes a flexible resource aggregation method for multi-type renewable powered 5G communication base station clusters and a coordinated scheduling strategy for participating in power system peak shaving.First,the adjustable power consumption characteristics of multiple types of base stations under the sleep mechanism and the regulating capacity of energy storage considering the reserve power of the base station are analyzed.A flexibility space quantification model considering the impact of the uncertainty of solar power generation and base station communication load on the power feasible region of flexible resources for renewable powered 5G base stations is formulated based on the idea of limit scenarios.The flexible resource aggregation adjustable domain of a massive base station cluster is obtained using the Minkowski sum method to depict the spatio-temporal coupled energy trajectory of heterogeneous base station flexibility resources.Second,an optimal scheduling optimization model for base station flexibility resources participating in the electric energy market and auxiliary service market is established.Also a hierarchical distributed day-ahead peak shaving scheduling strategy based on the ADMM algorithm is proposed.The problem of large-scale base station cluster scheduling is decomposed into three sub-problems:unified collaborative peak shaving power response,aggregated power autonomous scheduling,and base station cluster power allocation for an iterative solution.Through the simulation test and comparative analysis,the proposed strategy can reduce the energy cost of communication base stations by 69.86%.This provides an effective means to improve the utilization of communication resources and the flexible regulation capability of the power system.