计及5G基站运行协同的分布式储能优化配置方法

doi:10.19595/j.cnki.1000-6753.tces.231450

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摘要

通信基站普遍配有备电储能,且其大多数时间处于闲置状态。随着5G基站的加速建设,与之而来的大量备电储能对配电网来说将是十分可观的灵活性资源。为实现资源的充分利用,探究5G基站储能参与配电网灵活调控的潜力具有重要意义。在此背景下,本文提出一种计及5G基站储能协同的分布式储能（Distributed Energy Storage, DES）优化配置方法：首先,通过对5G基站的负荷特性及灵活储能容量进行分析,提出了含5G基站储能的配电网“规划-运行”双层优化模型。其中,规划层以网络年综合成本最小为目标,对DES进行选址定容;运行层以电压综合水平最优为目标,对DES与基站储能的调度策略进行寻优。为对该模型进行高效求解,提出了一种适用于大量异质变量的多目标动态评价优化算法,该算法通过对变量分组并在求解过程中自适应调整目标函数的选取,以加快求解速度、提高搜索精度。仿真结果证明了所提出的DES协同优化配置方法在降低成本和促进新能源消纳方面的有效性,以及所提出优化算法在兼顾多目标与快速求解方面的优越性。

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关键词 ：分布式储能, 优化配置, 5G基站, 规划运行协同, 多目标动态评价

Abstract：

Communication base stations (BSs) are normally equipped with backup energy storages, which are idle in most of the time. As the construction of 5G BSs is accelerating, their backup energy storages become prospective flexible resources to electrical distribution networks. To fully utilize these energy storage resources, it is of great significance to explore their capability in participating in the flexible dispatching of distribution networks. In this context and under the background of increasing penetrations of renewable generations, an optimal configuration method for distributed energy storage (DES) considering the coordinated operation of 5G BS energy storage is proposed, which improves the voltage profiles of distribution networks, facilitates the accommodation of renewable generations and minimizes the investment cost of DES.
Firstly, by analyzing the load characteristic and the flexible energy storage capacity of 5G BS, the model of 5G BS participating in distribution network operation is constructed. The charging/discharging cost of 5G BS energy storage is also analyzed. Next, the optimal configuration method for DES considering the coordinated operation of 5G BS energy storage is proposed. This method adopts a distribution network “planning-operating” two-layer model, where the planning layer aims to minimize the network annual cost by sitting and sizing DES, and the operating layer aims to optimize the network comprehensive voltage level by dispatching the DES and 5G BS energy storage. Considering such two-layer model contains massive and heterogenous decision variables, an optimization algorithm based on multi-objective dynamic assessment considering massive heterogenous variables (DA-H) is designed. The DA-H algorithm groups the decision variables according to their properties, and searches for the optima through divide-and-conquer. By assigning the membership function for each objective, dynamic assessments are performed to determine the fitness value of each solution during iterations. This aims to allocate more searching resources to the objective function that requires greater improvement, and the final optimal solution is an equilibrium one located on the Pareto frontier.
Finally, to validate the effectiveness and efficiency of the proposed method, case studies are carried out on the improved IEEE 33-bus system. Simulation results show that, by using the proposed DES configuration method, the network annual comprehensive cost equivalent to per day is 567.00 yuan, including 407.40 yuan of network power losses and 159.60 yuan of DES investment and operation costs. Compared with the case where 5G BS energy storage does not participate in network dispatching, the comprehensive cost decreases by 31.6%, where a decrease of 36.1% is achieved in DES investment and operation costs, and a decrease of 29.6% is achieved in network power losses. The costs of 5G BS before and after participating in distribution network dispatching is also compared, which demonstrates that 5G BS operators have sufficient willingness to get involved. To validate the advances of the proposed DA-H algorithm, its optimization performance is compared with improved multi-objective PSO algorithm and single-objective optimization. Results show that the DA-H algorithm achieves a balance among multiple voltage objectives. Although its performance along a single objective achieves a slight decrease, its performance along the other objectives are superior to the ones obtained in single-objective optimization. Additionally, the DA-H algorithm has advantages in solving speed and accuracy compared to other algorithms.

Key words： Distributed energy storage（DES） optimal configuration 5G base station coordinated planning and operation multi-objective dynamic assessment

收稿日期: 2023-09-01

PACS:

TM732

基金资助:

中央高校基本科研业务费专项资金资助项目（2022MS002）

通讯作者: 祁琪,女,1992年生,博士,硕士生导师,研究方向为电力系统分析与控制、主动配电网规划与优化运行、智能用电等E-mail: qigx0521@163.com

作者简介: 毕皓淳,男,2000年生,硕士研究生,研究方向为主动配电网规划与优化运行。E-mail：13031195613@163.com

引用本文:

毕皓淳, 祁琪, 刘向军, 侯子豪, 艾欣. 计及5G基站运行协同的分布式储能优化配置方法[J]. 电工技术学报, 0, (): 9041-41. Bi Haochun, Qi Qi, Liu Xiangjun, Hou Zihao, Ai Xin. An Optimal Configuration Method for DES Considering Coordinated Operation of 5G Base Station. Transactions of China Electrotechnical Society, 0, (): 9041-41.

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