上海交通大学学报

上海交通大学学报 >

2025 , Vol. 59 >Issue 11: 1603 - 1617

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2024.020

新型电力系统与综合能源

考虑5G基站可调度备用储能和智能软开关的主动配电网协同优化调度方法

  • 高崇 ,
  • 段瑶 ,
  • 程苒 ,
  • 陈沛东 ,
  • 周姝灿 ,
  • 张沈习 ,
  • 陈玮林 ,
  • 刘志文
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  • 1 广东电网有限责任公司电网规划研究中心, 广州 510308
    2 上海交通大学 电力传输与功率变换控制教育部重点实验室, 上海 200240
    3 南方电网能源发展研究院有限责任公司, 广州 510670
高 崇(1983—),高级工程师,从事电力系统规划与运行方面的研究.
张沈习,副研究员,博士生导师;E-mail:willzsx@163.com.

收稿日期: 2024-01-12

  修回日期: 2024-03-28

  录用日期: 2024-04-10

  网络出版日期: 2024-05-01

基金资助

中国南方电网有限责任公司科技项目(GDKJXM20220273);国家自然科学基金项目(U22B20114)

收起

Collaborative Optimization Scheduling Method for Active Distribution Networks Considering Dispatchable Backup Batteries of 5G Base Station and Soft Open Point

  • GAO Chong ,
  • DUAN Yao ,
  • CHENG Ran ,
  • CHEN Peidong ,
  • ZHOU Shucan ,
  • ZHANG Shenxi ,
  • CHEN Weilin ,
  • LIU Zhiwen
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  • 1 Grid Planning and Research Center, Guangdong Power Grid Co., Ltd., Guangzhou 510308, China
    2 Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
    3 Energy DevelopmentResearch Institute, China Southern Power Grid, Guangzhou 510670, China

Received date: 2024-01-12

  Revised date: 2024-03-28

  Accepted date: 2024-04-10

  Online published: 2024-05-01

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摘要

随着以风电、光伏为主的分布式电源在终端能源消费中占比不断提升,充分调度电网内部的灵活性资源、提升主动配电网(ADN)的调控能力具有重要意义.为此,提出一种考虑5G基站可调度备用储能和智能软开关的ADN协同优化调度方法.首先,分析5G基站功耗模型,建立计及5G基站通信负载和ADN供电节点可靠性的备用储能容量评估模型.在此基础上,以最小化ADN综合运行费用为目标函数,综合考虑风电、光伏出力和负荷需求的不确定性,构建基于机会约束的ADN协同优化调度模型.为提高模型求解效率,采用二阶锥松弛和基于拉丁超立方采样的机会约束确定性转化法,将模型转化为混合整数二阶锥规划问题.最后,通过IEEE 33节点ADN算例验证了所提方法的可行性和有效性.

关键词： 主动配电网; 5G基站备用储能; 灵活性资源; 智能软开关; 机会约束

本文引用格式

高崇 , 段瑶 , 程苒 , 陈沛东 , 周姝灿 , 张沈习 , 陈玮林 , 刘志文 . 考虑5G基站可调度备用储能和智能软开关的主动配电网协同优化调度方法[J]. 上海交通大学学报, 2025 , 59(11) : 1603 -1617 . DOI: 10.16183/j.cnki.jsjtu.2024.020

Abstract

As the proportion of distributed generation, mainly wind turbine generation and photovoltaic, in terminal energy consumption increases, it is of great significance to fully utilize the flexibility resources within power grids and enhance the regulation capability of active distribution networks (ADN). To this end, an ADN collaborative optimization scheduling method is proposed considering dispatchable backup battery of 5G base station (BS) and soft open point. First, an analysis of the power consumption model of 5G BS is conducted, leading to the establishment of a backup battery capacity evaluation model which considers the communication load of 5G BS and the reliability of ADN nodes. Based on this and taking the minimization of the comprehensive operating cost of ADN as the objective function, considering the uncertainty of wind power, photovoltaic output, and load demand, an ADN collaborative optimal scheduling model based on chance constraints is developed. A second-order cone relaxation and a chance-constrained determinization approach based on Latin hypercube sampling are employed to enhance the solution efficiency of the model, which transforms the model into a mixed-integer second-order cone programming problem. Finally, the feasibility and effectiveness of the proposed method are verified by the IEEE 33-bus ADN case.

Key words： active distribution network (ADN); 5G base station backup battery; flexible resource; soft open point; chance constraint

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