A Two-stage Configuration Optimization Model for BESS in Distribution Networks Based on Line Loss Sensitivity

王彬; 王学军; 葛磊蛟; 刘航旭; 魏联滨; 王莹

doi:10.19725/j.cnki.1007-2322.2023.0410

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

A Two-stage Configuration Optimization Model for BESS in Distribution Networks Based on Line Loss Sensitivity

更新时间：2026-02-02

- A Two-stage Configuration Optimization Model for BESS in Distribution Networks Based on Line Loss Sensitivity
- Vol. 43, Issue 1, Pages: 72-80(2026)
- 作者机构：
  
  1. 国网天津市电力公司, 天津市河北区,300010
  2. 天津大学电气自动化与信息工程学院, 天津市南开区,300072
- 作者简介：
- 基金信息：
- DOI：10.19725/j.cnki.1007-2322.2023.0410
  CLC： 1
- Published：2026
- 稿件说明：
移动端阅览
王彬, 王学军, 葛磊蛟, et al. A Two-stage Configuration Optimization Model for BESS in Distribution Networks Based on Line Loss Sensitivity[J]. 2026, 43(1): 72-80.
DOI：

王彬, 王学军, 葛磊蛟, et al. A Two-stage Configuration Optimization Model for BESS in Distribution Networks Based on Line Loss Sensitivity[J]. 2026, 43(1): 72-80. DOI： 10.19725/j.cnki.1007-2322.2023.0410.

摘要

光伏（photovoltaics

PV）和电动汽车（electric vehicles

EV）的发展加剧了配电网的运行压力，尽管接入电池储能系统（battery energy storage systems

BESS）可以缓解该现象，但现有的优化配置模型较少考虑BESS接入位置对线损的影响。针对上述挑战，提出一个二阶段优化配置模型。该模型基于线损敏感度，旨在优化含高比例光伏和电动汽车的配电网中电池储能系统的配置。首先，构建基于线损敏感度的BESS接入位置优化选取模型；之后，在BESS接入容量优化方面，建立考虑运维成本、线损、调压和负荷峰值等目标的容量优化模型；并提出改进的粒子群优化算法对所提问题进行优化求解。所提方法在含高比例PV-EV的IEEE-33节点配电网上进行评估。从目标函数、系统效率、投资回收期和统计分析等方面对几种算法结果进行了比较。仿真结果表明，基于线损敏感度的高比例PV-EV配电网的BESS二阶段优化配置模型可以更好地降低线损、改善电压分布，使系统成本降低40.05%，线损降低10.67%，负荷峰值降低12.05%，验证了所提方法的有效性。

Abstract

The development of photovoltaics (PV) and electric vehicles (EV) has intensified the operational pressure of the distribution network. Although the integration of battery energy storage systems (BESS) can alleviate this situation

existing configuration optimization models rarely consider the impact of BESS integration location on line loss. To address this issue

in this paper we propose a two-stage configuration optimization model for BESS based on line loss sensitivity in distribution networks with high proportions of PV and EV. The first step involves the construction of a BESS access location optimal selection model based on line loss sensitivity. Afterwards

in terms of BESS access capacity optimization

a capacity optimization model is established considering objectives such as operation and maintenance costs

line losses

voltage regulation

and peak load. Moreover

we propose an improved particle swarm optimization algorithm to optimize and solve the model. The proposed method is evaluated on an IEEE-33 node distribution network with a high proportion of PV-EV. The results obtained by the considered algorithms are compared in terms of objective function

system efficiency improvement

investment payback period

and statistical analysis. The simulation results demonstrate that the two-stage configuration optimization for BESS in high proportion PV-EV distribution network based on line loss sensitivity model can effectively reduce line loss

improve voltage distribution

and reduce system cost by 40.05%

line loss by 10.67%

and load peak by 12.05%

thereby verifying the effectiveness of the proposed method.

关键词

Keywords

references

RAIHAN A, TUSPEKOVA A. Dynamic impacts of economic growth, energy use, urbanization, tourism, agricultural value-added, and forested area on carbon dioxide emissions in Brazil[J]. Journal of Environmental Studies and Sciences, 2022, 12(4): 794−814.

ZENG Zilong, LI Yong, LI Peiqiang, et al . Distributional robust configuration of energy storage considering risk management and multi-stage security correction[J ] . High Voltage Engineering, 2023, 49(10): 4150−4162(in Chinese).

曾子龙, 李勇, 李培强, 等. 综合多阶段安全校正与风险管控的储能分布鲁棒优化配置[J]. 高电压技术, 2023, 49(10): 4150−4162.

ZHENG Yuanshuo, LI Feng, DONG Jiuling, et al . Optimal dispatch strategy of spatio-temporal flexibility for electric vehicle charging and discharging in vehicle-road-grid mode[J ] . Automation of Electric Power Systems, 2022, 46(12): 88−97(in Chinese).

郑远硕, 李峰, 董九玲,等. “车-路-网”模式下电动汽车充放电时空灵活性优化调度策略[J]. 电力系统自动化, 2022, 46(12): 88−97.

DABBAGHJAMANESH M, MOEINI A, KAVOUSI-FARD A. Reinforcement learning-based load forecasting of electric vehicle charging station using Q-learning technique[J]. IEEE Transactions on Industrial Informatics, 2021, 17(6): 4229−4237.

LI Yuanzheng, HAO Guokai, LIU Yun, et al . Many-objective distribution network reconfiguration via deep reinforcement learning assisted optimization algorithm[J ] . IEEE Transactions on Power Delivery, 2022, 37(3): 2230−2244.

CHEN Hanyang, LIU Yang, XU Lixiong, et al . Optimal configuration of shared energy storage on residential user side considering capacity reduction[J ] . Electric Power Construction, 2023, 44(09): 43-57(in Chinese).

陈寒阳, 刘洋, 许立雄, 等. 考虑容量削减的居民用户共享储能优化配置[J]. 电力建设, 2023, 44(09): 43-57.

WU Xiong, HE Mingkang, HE Wenwen, et al . Optimal capacity of a wind-solar-thermo-storage-bundled power transmission system considering battery life[J ] . Power System Protection and Control, 2023, 51(15): 66−75(in Chinese).

吴雄, 贺明康, 何雯雯, 等. 考虑储能寿命的风-光-火-储打捆外送系统容量优化配置[J]. 电力系统保护与控制, 2023, 51(15): 66−75.

WANG Fengxue, OUYANG Sen, XIN Xi. Optimal configuration of user-side energy storage considering power supply transaction mode and capacity market[J]. High Voltage Engineering, 2023, 49(07): 2785−2795(in Chinese).

王凤学, 欧阳森, 辛曦. 计及保供电交易模式和容量市场的用户侧储能优化配置[J]. 高电压技术, 2023, 49(07): 2785−2795.

LU Qiuyu, MA Qianli, WEI Wei, et al . Optimal configuration of energy storage parameters based on confidence capacity of wind farms[J ] . Transactions of China Electrotechnical Society, 2022, 37(23): 5901−5910(in Chinese).

陆秋瑜, 马千里, 魏韡, 等. 基于置信容量的风场配套储能容量优化配置[J]. 电工技术学报, 2022, 37(23): 5901−5910.

FATHY A. A novel artificial hummingbird algorithm for integrating renewable based biomass distributed generators in radial distribution systems[J]. Applied Energy, 2022, 323: 119605.

TOLBA M A, HOUSSEIN E H, EISA A A, et al . Optimizing the distributed generators integration in electrical distribution networks: efficient modified forensic-based investigation[J ] .Neural Computing and Applications, 2023, 35(11): 8307−8342.

JAYASEKARA N, MASOUM Mohammad A S, WOLFS P J. Optimal operation of distributed energy storage systems to improve distribution network load and generation hosting capability[J]. IEEE Transactions on Sustainable Energy, 2016, 7(1): 250−261.

KHUNKITTI S, BOONLUK P, SIRITARATIWAT A. Optimal location and sizing of bess for performance improvement of distribution systems with high DG penetration[J]. International Transactions on Electrical Energy Systems, 2022, 2022: 1−16.

JANAMALA V, REDDY D. Coyote optimization algorithm for optimal allocation of interline—Photovoltaic battery storage system in islanded electrical distribution network considering EV load penetration[J]. Journal of Energy Storage, 2021, 41: 102981.

WANG Zeshuang, CHEN Jiajun, ZH U Jianquan, et al . Optimal configuration and operation strategy of energy storage considering cycle life[J ] . Electric Power Automation Equipment, 2021, 41(10): 75−81(in Chinese).

王泽爽, 陈嘉俊, 朱建全, 等. 计及循环寿命的储能优化配置与运营策略[J]. 电力自动化设备, 2021, 41(10): 75−81.

BOONLUK P, KHUNKITTI S, Fuangfoo P, et al . Optimal siting and sizing of battery energy storage: Case study seventh feeder at Nakhon Phanom substation in Thailand[J ] . Energies, 2021, 14(5): 1458.

SATYANARAYANA S, RAMANA T, SIVANAGARAJU S, et al . An efficient load flow solution for radial distribution network including voltage dependent load models[J ] . Electric Power Components and Systems, 2007, 35(5): 539−551.

GHORBANI N, KASAEIAN A, TOOPSHEKAN A, et al . Optimizing a hybrid wind-PV-battery system using GA-PSO and MOPSO for reducing cost and increasing reliability[J ] . Energy, 2018, 154: 581−591.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Energy Storage Optimization Configuration of Distribution Network Considering Microgrid Clusters and System Economic Operation

Active Power Coordination Method for Distributed Generation in Distribution Networks with DG and EV Based on Second\|order Cone Programming

A Method to Evaluate Flexibility of Distribution Network Considering Grid-Connection of Electric Vehicles

Coordination Optimization of Distribution Network Considering Hydro-photovoltaic-load Uncertainty

Power Restoration Decision and Generalized Dynamic Islanding Strategy After Distribution Network Failure Considering Operational Risks

Related Author

Shizhen WANG

Xun DOU

Jun WANG

WU Jiekang

WU Zhishan

LIN Yixin

YAN Shaowei

CHEN Zhonghua

Related Institution

School of Electrical Engineering and Control Science, Nanjing Tech University

NARI Group Corporation

School of Automation, Guangdong University of Technology

Hangzhou Electric Power Design Institute Co., Ltd.

Hangzhou Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd.

AI问答

⁰