Multi-objective Optimization Model an Intelligent Solution Algorithm for Hierarchical Protection Location Selection in Distribution Networks

DAI Zhihui; LIU Junyi; LUAN Kun; NING Zhiheng; DING Yangtian; YANG Qiyue; CAO Haiou

doi:10.20204/j.sp.2026.04008

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Multi-objective Optimization Model an Intelligent Solution Algorithm for Hierarchical Protection Location Selection in Distribution Networks

更新时间：2026-04-20

- Multi-objective Optimization Model an Intelligent Solution Algorithm for Hierarchical Protection Location Selection in Distribution Networks
- Vol. 54, Issue 4, Pages: 61-69(2026)
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- DOI：10.20204/j.sp.2026.04008
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- Published：2026
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戴志辉,刘钧溢,栾琨,宁志恒,丁扬天,杨骐跃,曹海欧.配电网分级保护选点的多目标优化模型及智能求解算法[J].智慧电力,2026,54(4):61-69.

doi:10.20204/j.sp.2026.04008
戴志辉,刘钧溢,栾琨,宁志恒,丁扬天,杨骐跃,曹海欧.配电网分级保护选点的多目标优化模型及智能求解算法[J].智慧电力,2026,54(4):61-69. DOI： 10.20204/j.sp.2026.04008.

doi:10.20204/j.sp.2026.04008 DOI：

摘要

针对现有配电网分级保护选点配置缺乏定量模型、配置方案依赖专家经验且合理性难以量化评估的问题，为满足分级保护的多维需求，提出一种配电网分级保护选点的多目标优化方法。通过量化保护装置间的配合关系、保护配置数量以及主干线保护安装位置等约束，构建了以保护动作时间、故障失负荷及保护设备总投资最小为目标的优化模型。采用改进的多目标骨干粒子群算法（BB-MOPSO）求解模型，并综合运用K-means聚类、最小-最大归一化及线性期望值法从解集中筛选出最终配置方案。在MATLAB中基于IEEE 33节点配电网的仿真结果表明，所提方法能有效提升保护动作的速动性与选择性，提高配电网规划的安全性和经济性。

Abstract

To address the issues that existing configurations for hierarchical protection location selection in distribution networks lack a quantitative model

rely heavily on expert experience

and have insufficient quantitative evaluation of configuration rationality

a multi-objective optimization method for hierarchical protection location selection is proposed to meet the multi-dimensional requirements. By quantifying constraints such as the coordination relationships between protection devices

the number of protection configurations

and the installation locations of protection on main feeders

an optimization model is established with the objectives of minimizing protection operation time

fault-induced load loss

and the total investment cost of protection equipment. An improved bare-bones multi-objective particle swarm optimization （BB-MOPSO） algorithm is employed to solve the model and obtain the Pareto-optimal solution set. The final configuration scheme is then selected from this set by integrating the K-means clustering algorithm

min-max normalization

and the linear desirability function. Simulation results based on an IEEE 33-node distribution network model in MATLAB demonstrate that the proposed method can effectively enhance the speed and selectivity of protection operation

thereby improving both the security and economy of distribution network planning.

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references

余贻鑫，栾文鹏. 智能电网述评 [J ] . 中国电机工程学报，2009，29（34）：1-8.

曹金铭，范开俊，徐丙垠，等. 基于容量边界值的高比例逆变型分布式电源配电网三级保护适用性分析 [J ] . 电网技术，2024，48（8）：3438-3448.

罗龙波，陈明辉，王雯沁，等. 考虑分级重构的配电网安全低碳两阶段运行优化方法 [J ] . 电力系统保护与控制，2024，52（14）：36-45.

燕鹏飞，杨知方，林伟，等. 计及多维紧急负荷调控目标的智能用电开关设备优化配置 [J ] . 电力系统保护与控制，2025，53（22）：162-174.

中华人民共和国国家发展和改革委员会. 3~110 kV 电网继电保护装置运行整定规程：DL/T 584—2007 [S ] . 北京：中国电力出版社，2007.

中国电力企业联合会. 继电保护和安全自动装置技术规程：GB/T 14285-2023 [S ] . 北京：中国标准出版社，2023.

中国南方电网有限责任公司. 110 kV 以下配电网装备技术导则：Q/C SG 10703—2009 [S ] . 北京：中国电力出版社，2009.

徐丙垠. 现代配电网继电保护技术及其发展 [J ] . 供用电，2024， 41（8）：65-74，87.

王启明. 山东配电网层次化保护技术研究与应用 [D ] . 济南：山东大学，2019.

栾琨，戴志辉，史琛. 应对10kV配电网电流保护失配问题的整定优化方案 [J ] . 电力系统保护与控制，2024，52（15）：155-166.

YAZDANINEJADI A，GOLSHANNAVAZ S，NAZARPOUR D，et al. Dual-setting directional overcurrent relays for protecting automated distribution networks [J ] . IEEE Transactions on Industrial Informatics，2019，15（2）：730-740.

YANG B，TANG J，FENG C，et al. Optimal setting method of inverse time overcurrent protection for the distribution networks based on the improved grey wolf optimization [J ] . Complexity，2021（1）：1-9.

赵宇，李谦，张云晓，等. 含分布式能源配电网中考虑供电可靠性的混合储能优化配置 [J ] . 智慧电力，2024，52（8）：25-32，49.

刘伟生. 配电网层次化保护技术及工程应用 [D ] . 济南：山东大学，2022.

国家能源局. 电力系统继电保护设计技术规范：DL/ T 5506-2015 [S ] . 北京：中国计划出版社，2015.

TANG M，LU H，LI B. Fault location of untransposed double-circuit transmission lines based on an improved Karrenbauer matrix and the QPSO algorithm [J ] . Protection and Control of Modern Power Systems，2023，8（3）：738-751.

LIU H，LEI Y，FU Y，et al. A novel hybrid-point-line energy management strategy based on multi-objective optimization for range-extended electric vehicle [J ] . Energy，2022，247

程雄，戴鹏，钟浩，等. 考虑综合相似性度量的光伏典型出力场景聚类方法 [J ] . 中国电机工程学报，2024，44（21）：8462-8475.

LIU F，DENG Y，Determine the number of unknown targets in the open world based on elbow method[J ] . IEEE Transactions on Fuzzy Systems，2021，29（5）：986-995 .

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