区段定位性能提升角度下弹性配电网灾前强化方法

doi:10.19595/j.cnki.1000-6753.tces.260285

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摘要

台风灾害易引发配电网量测信息畸变,配电网故障区段定位在信息不完备条件下的准确性直接决定灾中响应和灾后恢复效率,现有区段定位方法未融合灾前强化信息导致其性能提升受限,因此,如何从区段定位性能提升角度决策配电网灾前强化方案成为灾中响应和灾后恢复效率的关键科学问题。对此,本文提出一种区段定位性能提升角度下弹性配电网灾前强化方法。首先,基于Batts风场模型和路径模型,构建台风灾害下区段故障与FTU故障概率模型,并采用蒙特卡洛方法生成灾害场景集,结合K-medoids聚类方法进行场景缩减。其次,引入 ε-约束法,在保证定位性能的前提下,构建以综合优化代价最小化为目标的区段定位-灾前强化协同优化模型,其中综合优化代价由强化投资成本与运行损失构成。进一步,设计基于 ε-约束的两阶段贪心搜索求解方法。最后,以33节点双端供电配电网为算例进行仿真验证,并在不同规模系统中验证方法的适用性。结果表明：在有限投资约束下,所提方法能够显著提升区段定位性能,并在保证较高定位性能的同时有效控制综合优化代价,实现定位性能与经济性的协调优化,从而增强配电网在极端灾害环境下的弹性。

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	王秋杰
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	随权

关键词 ：台风灾害, 弹性配电网, 区段定位, 灾前强化, 场景缩减

Abstract：

Under typhoon disasters, distribution networks are prone to experiencing complex multiple faults and measurement information distortion of feeder terminal units (FTUs), which significantly reduces the accuracy of section location under incomplete information conditions. Existing studies typically treat section location and pre-disaster reinforcement as separate problems, failing to capture the coupled effects of fault uncertainty and information distortion on reinforcement decision-making, and thus cannot effectively guide reinforcement strategies from the perspective of section location performance. To address this issue, a pre-disaster reinforcement method for resilient distribution networks is developed from the perspective of improving section location performance. Section location performance is explicitly incorporated into the reinforcement decision-making process, enabling coordinated optimization between the physical structure and the information layer.
First, the spatial topology structure of the distribution network is combined with the Batts wind field model and typhoon track model to calculate the equivalent wind speed of distribution network components, and probabilistic models for section faults and FTU faults are established. Next, the Monte Carlo method is employed to generate disaster scenario sets containing both section fault states and information distortion states, and the K-medoids clustering method is adopted for scenario reduction to reduce the computational scale. On this basis, decision variables for section and FTU reinforcement are introduced, and reinforcement effects are characterized through the modification of fault and distortion probabilities. A section location model is established based on switching functions and the minimum set theory, combined with constraints including fault multiplicity, measurement consistency, and protection information, to achieve fault identification under complex conditions. Furthermore, a probability-weighted section location accuracy index is defined to evaluate performance across multiple scenarios. A coordinated optimization model is then formulated with the objective of minimizing the overall optimization cost, which consists of reinforcement investment cost and the economic loss converted from expected energy not supplied. The ε-constraint method is adopted to transform the problem into a single-objective formulation while ensuring that section location performance is not lower than a predefined threshold. To address computational complexity, a two-stage greedy search method is designed to iteratively screen and optimize reinforcement schemes.
Case studies are conducted on a 33-bus dual-end fed distribution network and a 10-bus system. The results show that, as reinforcement investment increases, section location accuracy improves, while expected energy not supplied and overall optimization cost decrease, both exhibiting diminishing marginal benefits. Under limited investment constraints, reinforcement measures tend to prioritize sections with high fault probabilities and critical topological positions, as well as key FTUs that significantly affect fault identification. Comparative analysis of different reinforcement strategies indicates that reinforcing only FTUs improves information quality but has limited impact on reducing operational losses, while reinforcing only sections effectively reduces fault uncertainty and significantly decreases energy not supplied. Coordinated reinforcement of sections and FTUs achieves higher section location accuracy under complex scenarios while maintaining a reasonable economic performance. Sensitivity analysis further shows that the section location performance constraint level has a significant impact on reinforcement decisions and cost distribution.
By incorporating section location performance constraints into pre-disaster reinforcement decision-making, the proposed method enables coordinated modeling and optimization of fault uncertainty and information distortion. Case study results show that: (1) Under limited investment constraints, the proposed method improves section location accuracy and reduces the impact of location uncertainty on operational losses, with consistent improvement trends observed across systems of different scales. (2) Section reinforcement and FTU reinforcement act on fault occurrence probability and information reliability, respectively, and their coordinated implementation simultaneously suppresses fault uncertainty and information distortion, thereby enhancing the stability of section location results under complex scenarios. (3) The section location performance constraint parameter regulates reinforcement decisions, and its variation affects the trade-off between reinforcement investment and operational losses, thereby influencing the selection of the optimal reinforcement scheme.

Key words： Typhoon disasters resilient distribution networks section location pre-disaster reinforcement scenario reduction

收稿日期: 2026-02-15

PACS:

TM73

基金资助:

国家自然科学基金资助项目（52307109）

通讯作者: 谭洪男,1991年生,博士,硕士生导师,研究方向为综合能源系统优化运行与规划。E-mail：tanhong@ctgu.edu.cn

作者简介: 王秋杰男,1988年生,博士,硕士生导师,研究方向为综合能源系统优化调度、弹性配电网等。E-mail：wangqiujie@ctgu.edu.cn

引用本文:

王秋杰, 张纵泽, 谭洪, 甘德伟, 随权. 区段定位性能提升角度下弹性配电网灾前强化方法[J]. 电工技术学报, 0, (): 285-. Wang Qiujie, Zhang Zongze, Tan Hong, Gan Dewei, Sui Quan. Pre-disaster reinforcement method for resilient distribution networks from the perspective of improving section location performance. Transactions of China Electrotechnical Society, 0, (): 285-.

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